-----------------------------------------------------------------------------------------------------------------
      name:  <unnamed>
       log:  C:\Users\scripts\Downloads\main-models-stata.log
  log type:  text
 opened on:  27 Jan 2025, 15:38:57

. 
. * Set plot scheme
. set scheme plottig

. graph set window fontface "LM Roman 10"

. graph set print fontface "LM Roman 10"

. graph set svg fontface "LM Roman 10"

. 
. * ssc install grstyle
. 
. grstyle clear

. grstyle init

. grstyle set plain, box

. grstyle color background white

. 
. * ssc install palettes
. 
. grstyle set color Set1

. grstyle yesno draw_major_hgrid yes

. grstyle yesno draw_major_ygrid yes

. grstyle color major_grid gs8

. grstyle linepattern major_grid dot

. grstyle set legend 4, box inside

. grstyle color ci_area gs12%50

. 
. * Load data
. use "ads_imgs_vids.dta", clear

. 
. 
. * Reformat party family var
. tab pg_party_family_name

pg_party_family_nam |
                  e |      Freq.     Percent        Cum.
--------------------+-----------------------------------
           Agrarian |        436        0.69        0.69
Christian democracy |     10,921       17.40       18.09
Communist/Socialist |      2,215        3.53       21.62
       Conservative |      9,274       14.77       36.40
    Green/Ecologist |      7,298       11.63       48.02
            Liberal |     15,000       23.90       71.92
         Right-wing |      1,038        1.65       73.57
   Social democracy |     15,077       24.02       97.59
      Special issue |      1,488        2.37       99.96
          no family |         25        0.04      100.00
--------------------+-----------------------------------
              Total |     62,772      100.00

. replace pg_party_family_name = "Christian_democracy" if pg_party_family_name == "Christian democracy"
(10,921 real changes made)

. replace pg_party_family_name = "Social_democracy" if pg_party_family_name == "Social democracy"
(15,077 real changes made)

. replace pg_party_family_name = "Green_Ecologist" if pg_party_family_name == "Green/Ecologist"
(7,298 real changes made)

. replace pg_party_family_name = "Right_wing" if pg_party_family_name == "Right-wing"
(1,038 real changes made)

. replace pg_party_family_name = "Communist_Socialist" if pg_party_family_name == "Communist/Socialist"
(2,215 real changes made)

. 
. 
. * ##############################################################################
. * MAIN MODELS
. * ##############################################################################
. 
. 
. *****************************
. * 1 - DV: Any woman on image/video, Controls: Audience age, number of faces
. *****************************
. 
. * Add number of ads per party
. quietly logit faces_any_fem i.only_women c.audience_avg_age c.nfaces i.parlgov_id, difficult // Quietly run mod
> el to use same observations 

. bysort parlgov_id: gen n_ads=_N if e(sample)
(90 missing values generated)

. 
. * Run regression 
. logit faces_any_fem i.only_women c.audience_avg_age c.nfaces i.parlgov_id [iweight=1/n_ads], cluster(parlgov_id
> )

Iteration 0:   log pseudolikelihood = -97.717909  
Iteration 1:   log pseudolikelihood = -72.780957  
Iteration 2:   log pseudolikelihood = -68.822263  
Iteration 3:   log pseudolikelihood = -68.531849  
Iteration 4:   log pseudolikelihood = -68.508322  
Iteration 5:   log pseudolikelihood = -68.507843  
Iteration 6:   log pseudolikelihood = -68.507842  

Logistic regression                                     Number of obs = 62,682
                                                        Wald chi2(2)  =      .
                                                        Prob > chi2   =      .
Log pseudolikelihood = -68.507842                       Pseudo R2     = 0.2989

                               (Std. err. adjusted for 151 clusters in parlgov_id)
----------------------------------------------------------------------------------
                 |               Robust
   faces_any_fem | Coefficient  std. err.      z    P>|z|     [95% conf. interval]
-----------------+----------------------------------------------------------------
    1.only_women |   .6626529   .1852815     3.58   0.000     .2995079    1.025798
audience_avg_age |   -.003354   .0047454    -0.71   0.480    -.0126548    .0059468
          nfaces |   1.208177   .1602126     7.54   0.000     .8941658    1.522188
                 |
      parlgov_id |
             47  |   1.649922   .2273273     7.26   0.000     1.204368    2.095475
             50  |   1.226989     .13304     9.22   0.000     .9662355    1.487743
            113  |   .5762969   .2216891     2.60   0.009     .1417943      1.0108
            118  |   2.115529   .1701596    12.43   0.000     1.782022    2.449035
            161  |    2.66355   .2679646     9.94   0.000     2.138349    3.188751
            196  |   3.168069   .1728539    18.33   0.000     2.829282    3.506857
            200  |   2.021339   .2518117     8.03   0.000     1.527798    2.514881
            220  |   1.062537   .1747721     6.08   0.000     .7199898    1.405084
            235  |   3.342735   .2805857    11.91   0.000     2.792797    3.892673
            256  |   1.849979   .1073656    17.23   0.000     1.639546    2.060412
            276  |   2.764586   .2272657    12.16   0.000     2.319153    3.210018
            280  |   2.646696   .2377653    11.13   0.000     2.180685    3.112708
            282  |   3.626739   .2317345    15.65   0.000     3.172548     4.08093
            306  |   3.167635   .2603836    12.17   0.000     2.657293    3.677978
            310  |   2.960503   .2506483    11.81   0.000     2.469242    3.451765
            311  |   1.638555   .2255911     7.26   0.000     1.196404    2.080705
            318  |   3.481809   .2545617    13.68   0.000     2.982878    3.980741
            345  |   2.879288   .2239497    12.86   0.000     2.440355    3.318222
            357  |   2.927606   .2591091    11.30   0.000     2.419761     3.43545
            360  |  -.1001385     .07677    -1.30   0.192    -.2506049    .0503279
            363  |   1.868758   .1671751    11.18   0.000     1.541101    2.196416
            376  |   1.717898   .2267188     7.58   0.000     1.273537    2.162258
            382  |   1.720105   .1469452    11.71   0.000     1.432098    2.008113
            395  |   3.637084   .1856535    19.59   0.000      3.27321    4.000958
            403  |   2.749546   .2029786    13.55   0.000     2.351715    3.147377
            417  |   1.626572   .1775878     9.16   0.000     1.278507    1.974638
            437  |   .7989317   .2063434     3.87   0.000     .3945061    1.203357
            438  |   3.340794   .1832263    18.23   0.000     2.981677    3.699911
            457  |   3.453605   .2029912    17.01   0.000     3.055749     3.85146
            467  |   2.490788   .1770788    14.07   0.000      2.14372    2.837856
            501  |   1.515843   .1506435    10.06   0.000     1.220587    1.811099
            512  |   1.947603   .2957134     6.59   0.000     1.368015     2.52719
            520  |   1.319098   .1637401     8.06   0.000     .9981738    1.640023
            528  |   3.610428   .3065406    11.78   0.000     3.009619    4.211236
            543  |   2.222367   .2710025     8.20   0.000     1.691212    2.753522
            558  |   2.273888   .2737301     8.31   0.000     1.737387    2.810389
            572  |   2.298029   .2296884    10.00   0.000     1.847848     2.74821
            581  |   2.189387    .220352     9.94   0.000     1.757505    2.621269
            585  |   2.836131   .2560406    11.08   0.000       2.3343    3.337961
            590  |   1.448271   .1922352     7.53   0.000     1.071497    1.825045
            596  |   .1354464   .2192428     0.62   0.537    -.2942615    .5651543
            600  |   .2790275   .1029238     2.71   0.007     .0773005    .4807546
            645  |    .669703   .2566023     2.61   0.009     .1667716    1.172634
            657  |   1.577714    .216137     7.30   0.000     1.154094    2.001335
            659  |   .4878423    .231907     2.10   0.035     .0333128    .9423717
            701  |   2.214048    .202131    10.95   0.000     1.817879    2.610218
            706  |   2.761955   .2214783    12.47   0.000     2.327865    3.196044
            723  |   2.851088   .2147106    13.28   0.000     2.430263    3.271913
            742  |   1.582028   .1557718    10.16   0.000      1.27672    1.887335
            756  |   2.138203   .2141863     9.98   0.000     1.718405       2.558
            757  |   2.526559   .2015488    12.54   0.000     2.131531    2.921588
            772  |   2.841807   .2292569    12.40   0.000     2.392472    3.291142
            773  |   3.448084   .2525698    13.65   0.000     2.953056    3.943111
            789  |   1.982387   .1677854    11.82   0.000     1.653533     2.31124
            791  |    2.75932   .2639564    10.45   0.000     2.241975    3.276665
            829  |   1.271056   .1516875     8.38   0.000     .9737536    1.568358
            851  |   .0348238   .1398331     0.25   0.803    -.2392441    .3088917
            865  |   1.844874   .2556836     7.22   0.000     1.343743    2.346004
            882  |   2.020224   .2194135     9.21   0.000     1.590181    2.450266
            892  |   2.141697   .2173499     9.85   0.000     1.715699    2.567695
            902  |   3.004298   .2488432    12.07   0.000     2.516574    3.492021
            904  |   1.933217   .2360644     8.19   0.000     1.470539    2.395894
            915  |   2.890994   .1983596    14.57   0.000     2.502217    3.279772
            945  |   2.424888   .2178928    11.13   0.000     1.997826     2.85195
            967  |   3.430934   .2020449    16.98   0.000     3.034934    3.826935
            969  |   1.319443   .2358351     5.59   0.000     .8572146    1.781671
            973  |   2.282323   .2412472     9.46   0.000     1.809487    2.755159
            984  |   3.107907   .1940233    16.02   0.000     2.727628    3.488185
            990  |   2.537908   .2850023     8.90   0.000     1.979313    3.096502
            993  |   1.361925    .163202     8.35   0.000     1.042055    1.681795
           1013  |  -1.406332   .0976576   -14.40   0.000    -1.597737   -1.214927
           1015  |   1.081067   .1538184     7.03   0.000     .7795885    1.382546
           1029  |   2.704969   .2120113    12.76   0.000     2.289434    3.120504
           1045  |   2.654176    .157181    16.89   0.000     2.346107    2.962245
           1062  |   3.474203   .2353322    14.76   0.000     3.012961    3.935446
           1072  |   1.362589   .1317866    10.34   0.000     1.104292    1.620886
           1110  |    3.05763   .2036471    15.01   0.000     2.658489    3.456771
           1118  |   .0248071   .2702233     0.09   0.927    -.5048209    .5544351
           1120  |   2.968086   .2559506    11.60   0.000     2.466432     3.46974
           1137  |   2.580257   .1818554    14.19   0.000     2.223826    2.936687
           1154  |   4.051752   .1774287    22.84   0.000     3.703998    4.399506
           1192  |   2.744091   .2413488    11.37   0.000     2.271056    3.217126
           1206  |   2.118863   .2832749     7.48   0.000     1.563654    2.674071
           1234  |   2.143123   .2203736     9.72   0.000     1.711198    2.575047
           1245  |   2.078941   .2002146    10.38   0.000     1.686528    2.471355
           1284  |   3.390683   .3383627    10.02   0.000     2.727504    4.053862
           1292  |   5.413307   .1887555    28.68   0.000     5.043353    5.783261
           1338  |   3.018323   .2973128    10.15   0.000     2.435601    3.601045
           1361  |    2.42697   .2041766    11.89   0.000     2.026791    2.827149
           1378  |   2.039954   .2128498     9.58   0.000     1.622776    2.457132
           1384  |  -2.347858   .3111982    -7.54   0.000    -2.957795   -1.737921
           1409  |   1.185095   .1712053     6.92   0.000     .8495387    1.520651
           1418  |   1.395941   .1097739    12.72   0.000     1.180788    1.611094
           1421  |   1.480693   .1735349     8.53   0.000     1.140571    1.820815
           1429  |   1.689396    .193899     8.71   0.000     1.309361    2.069431
           1432  |  -2.080232   .3578597    -5.81   0.000    -2.781624    -1.37884
           1436  |   1.456707   .1526636     9.54   0.000     1.157491    1.755922
           1448  |   4.058648   .1904862    21.31   0.000     3.685302    4.431994
           1461  |   4.553426   .2472116    18.42   0.000       4.0689    5.037952
           1463  |   4.451435   .2795369    15.92   0.000     3.903553    4.999317
           1465  |  -.1313705   .1798142    -0.73   0.465    -.4837998    .2210589
           1493  |   3.403641   .2158017    15.77   0.000     2.980678    3.826605
           1520  |  -3.715031   .5679874    -6.54   0.000    -4.828266   -2.601797
           1521  |   2.693536   .2181479    12.35   0.000     2.265974    3.121099
           1546  |   3.018543   .2808612    10.75   0.000     2.468065    3.569021
           1556  |   1.230898   .2370469     5.19   0.000      .766295    1.695502
           1573  |     4.9756   .2622383    18.97   0.000     4.461622    5.489577
           1575  |   1.596682   .1746154     9.14   0.000     1.254442    1.938922
           1582  |   3.523066   .1903124    18.51   0.000      3.15006    3.896071
           1591  |   1.168074   .1455445     8.03   0.000     .8828122    1.453336
           1592  |   2.940917   .2490991    11.81   0.000     2.452692    3.429142
           1594  |       2.91   .2196651    13.25   0.000     2.479464    3.340535
           1597  |   .5316491   .1803535     2.95   0.003     .1781628    .8851354
           1605  |   1.674572   .1793368     9.34   0.000     1.323078    2.026066
           1620  |   1.160158   .2904111     3.99   0.000     .5909624    1.729353
           1629  |   3.708368   .2119914    17.49   0.000     3.292872    4.123864
           1644  |   4.251532   .2393997    17.76   0.000     3.782317    4.720746
           1666  |    1.11226   .1358545     8.19   0.000     .8459898     1.37853
           1727  |   2.771822   .2885198     9.61   0.000     2.206334    3.337311
           1759  |   1.881863   .1527491    12.32   0.000      1.58248    2.181246
           1970  |    4.03967   .2534927    15.94   0.000     3.542833    4.536506
           2091  |   1.438438   .1353519    10.63   0.000     1.173153    1.703723
           2154  |   7.717033   .2165016    35.64   0.000     7.292698    8.141369
           2155  |    2.47312   .2428337    10.18   0.000     1.997175    2.949066
           2217  |   3.595855   .2019019    17.81   0.000     3.200135    3.991576
           2253  |    1.76066   .2371685     7.42   0.000     1.295819    2.225502
           2255  |   2.474301   .1911531    12.94   0.000     2.099648    2.848955
           2256  |   .5682356   .0735774     7.72   0.000     .4240266    .7124446
           2261  |   1.443306   .2095278     6.89   0.000      1.03264    1.853973
           2263  |   3.668202    .217978    16.83   0.000     3.240973    4.095431
           2337  |   2.793746   .1731297    16.14   0.000     2.454418    3.133074
           2341  |  -1.095322     .28654    -3.82   0.000     -1.65693   -.5337136
           2346  |   3.260134   .1306744    24.95   0.000     3.004017    3.516251
           2375  |   .9067091   .1019595     8.89   0.000     .7068721    1.106546
           2380  |   2.066847   .2640931     7.83   0.000     1.549234     2.58446
           2395  |    1.61898   .1222252    13.25   0.000     1.379424    1.858537
           2600  |   .1193129   .0684315     1.74   0.081    -.0148104    .2534361
           2623  |  -.0503001   .0796472    -0.63   0.528    -.2064057    .1058055
           2625  |   2.601209   .2102943    12.37   0.000     2.189039    3.013378
           2647  |    .128386   .2527625     0.51   0.612    -.3670195    .6237915
           2659  |   2.869492    .201477    14.24   0.000     2.474604    3.264379
           2668  |   2.765395   .1820305    15.19   0.000     2.408621    3.122168
           2670  |   1.692937   .2327213     7.27   0.000     1.236811    2.149062
           2717  |   .2569859   .1408519     1.82   0.068    -.0190788    .5330506
           2724  |   1.995979   .2354276     8.48   0.000     1.534549    2.457408
           2729  |   1.660714   .1770631     9.38   0.000     1.313676    2.007751
           2730  |    .147314   .2275834     0.65   0.517    -.2987412    .5933692
           2740  |   1.952024   .1766836    11.05   0.000     1.605731    2.298318
           2750  |   1.750622   .1239244    14.13   0.000     1.507735    1.993509
           2751  |  -.5517844   .1172918    -4.70   0.000    -.7816721   -.3218967
                 |
           _cons |  -4.013924   .3344559   -12.00   0.000    -4.669446   -3.358403
----------------------------------------------------------------------------------
Note: 0 failures and 47 successes completely determined.

. est store inter

. 
. * Calculate and save margins (plot in R)
. margins, at(only_women = (0 1)) saving("margins.dta", replace)

Predictive margins                                      Number of obs = 62,682
Model VCE: Robust

Expression: Pr(faces_any_fem), predict()
1._at: only_women = 0
2._at: only_women = 1

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   std. err.      z    P>|z|     [95% conf. interval]
-------------+----------------------------------------------------------------
         _at |
          1  |   .3450591   .0013007   265.28   0.000     .3425097    .3476085
          2  |    .448876   .0289613    15.50   0.000     .3921128    .5056392
------------------------------------------------------------------------------

. 
. * Run models for each party family
. levelsof pg_party_family_name if inlist(pg_party_family_name,  "Green_Ecologist","Communist_Socialist", "Social
> _democracy", "Christian_democracy", "Conservative", "Liberal", "Right_wing"), local(groups)
`"Christian_democracy"' `"Communist_Socialist"' `"Conservative"' `"Green_Ecologist"' `"Liberal"' `"Right_wing"' `
> "Social_democracy"'

. local estimates_list // 

. foreach g of local groups {
  2.         di "`g'"
  3.     quietly logit faces_any_fem i.only_women c.audience_avg_age c.nfaces i.parlgov_id [iweight=1/n_ads] if p
> g_party_family_name ==  "`g'", cluster(parlgov_id)
  4.         est store `g'   
  5. }
Christian_democracy
Communist_Socialist
Conservative
Green_Ecologist
Liberal
Right_wing
Social_democracy

. 
. * Output all models to latex table
. outreg2 [inter Green_Ecologist  Communist_Socialist Social_democracy Christian_democracy Conservative Liberal R
> ight_wing] using 1.xls, replace drop(i.parlgov_id) label excel tex alpha(0.001, 0.01, 0.05, 0.1) symbol(***, **
> , *, +)  dec(3) e(N_clust)
1.tex
1.xls
dir : seeout

. 
. 
. * Calculate and save margins (plot in R)
. levelsof pg_party_family_name if inlist(pg_party_family_name,  "Green_Ecologist","Communist_Socialist", "Social
> _democracy", "Christian_democracy", "Conservative", "Liberal"), local(groups)
`"Christian_democracy"' `"Communist_Socialist"' `"Conservative"' `"Green_Ecologist"' `"Liberal"' `"Social_democra
> cy"'

. local estimates_list // 

. foreach g of local groups {
  2.         di "`g'"
  3.    logit faces_any_fem i.only_women c.audience_avg_age c.nfaces i.parlgov_id [iweight=1/n_ads] if pg_party_f
> amily_name ==  "`g'", cluster(parlgov_id)
  4.         margins, at(only_women = (0 1) )  saving("`g'.dta", replace)
  5.         
. }
Christian_democracy

Iteration 0:   log pseudolikelihood = -10.510034  
Iteration 1:   log pseudolikelihood = -7.8809083  
Iteration 2:   log pseudolikelihood = -6.6508142  
Iteration 3:   log pseudolikelihood =  -6.347173  
Iteration 4:   log pseudolikelihood = -6.3421759  
Iteration 5:   log pseudolikelihood = -6.3421355  
Iteration 6:   log pseudolikelihood = -6.3421354  

Logistic regression                                     Number of obs = 10,921
                                                        Wald chi2(2)  =      .
                                                        Prob > chi2   =      .
Log pseudolikelihood = -6.3421354                       Pseudo R2     = 0.3966

                                (Std. err. adjusted for 16 clusters in parlgov_id)
----------------------------------------------------------------------------------
                 |               Robust
   faces_any_fem | Coefficient  std. err.      z    P>|z|     [95% conf. interval]
-----------------+----------------------------------------------------------------
    1.only_women |   .9367342   .5931918     1.58   0.114    -.2259004    2.099369
audience_avg_age |  -.0244865   .0225383    -1.09   0.277    -.0686609    .0196878
          nfaces |   1.965195   .5312308     3.70   0.000     .9240021    3.006389
                 |
      parlgov_id |
            235  |   2.162788   .3990883     5.42   0.000     1.380589    2.944986
            276  |   1.250145   .1399394     8.93   0.000     .9758693    1.524422
            282  |   2.162049   .2720722     7.95   0.000     1.628798    2.695301
            723  |   1.222691   .0462505    26.44   0.000     1.132042    1.313341
           1013  |  -4.284688   1.014166    -4.22   0.000    -6.272417   -2.296959
           1192  |   1.132185   .1049686    10.79   0.000     .9264503     1.33792
           1206  |   .7700869   .1885683     4.08   0.000     .4004999    1.139674
           1234  |   .4130832   .1064441     3.88   0.000     .2044566    .6217098
           1245  |   .2625105   .2057905     1.28   0.202    -.1408314    .6658525
           1361  |   .7536572   .0866732     8.70   0.000     .5837809    .9235336
           1432  |  -6.299533   1.890931    -3.33   0.001    -10.00569   -2.593377
           1463  |   3.256524   .4199135     7.76   0.000     2.433508    4.079539
           1727  |   1.423806   .2329495     6.11   0.000     .9672339    1.880379
           2395  |  -.4929948   .4299411    -1.15   0.252    -1.335664    .3496742
           2750  |   -.387227   .3103183    -1.25   0.212    -.9954396    .2209856
                 |
           _cons |  -2.192022   .8559261    -2.56   0.010    -3.869607    -.514438
----------------------------------------------------------------------------------
Note: 0 failures and 2 successes completely determined.

Predictive margins                                      Number of obs = 10,921
Model VCE: Robust

Expression: Pr(faces_any_fem), predict()
1._at: only_women = 0
2._at: only_women = 1

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   std. err.      z    P>|z|     [95% conf. interval]
-------------+----------------------------------------------------------------
         _at |
          1  |   .3618342   .0027895   129.71   0.000     .3563669    .3673015
          2  |   .4913467   .0830333     5.92   0.000     .3286044     .654089
------------------------------------------------------------------------------
Communist_Socialist

Iteration 0:   log pseudolikelihood =  -8.923319  
Iteration 1:   log pseudolikelihood = -7.1895664  
Iteration 2:   log pseudolikelihood = -7.1120881  
Iteration 3:   log pseudolikelihood = -7.1107533  
Iteration 4:   log pseudolikelihood = -7.1107529  

Logistic regression                                     Number of obs =  2,186
                                                        Wald chi2(2)  =      .
                                                        Prob > chi2   =      .
Log pseudolikelihood = -7.1107529                       Pseudo R2     = 0.2031

                                (Std. err. adjusted for 13 clusters in parlgov_id)
----------------------------------------------------------------------------------
                 |               Robust
   faces_any_fem | Coefficient  std. err.      z    P>|z|     [95% conf. interval]
-----------------+----------------------------------------------------------------
    1.only_women |  -.5002652   1.264977    -0.40   0.692    -2.979574    1.979043
audience_avg_age |  -.0335894   .0214273    -1.57   0.117    -.0755862    .0084073
          nfaces |   .9693992   .8013877     1.21   0.226     -.601292     2.54009
                 |
      parlgov_id |
            256  |  -.4564918   .3274062    -1.39   0.163    -1.098196    .1852126
            306  |   .6043388   .6487805     0.93   0.352    -.6672477    1.875925
            357  |   .7790505   .5031282     1.55   0.122    -.2070627    1.765164
            457  |   .6319106   .5480803     1.15   0.249     -.442307    1.706128
            572  |  -.1838438   .4854352    -0.38   0.705    -1.135279    .7675917
            791  |   .1565058   .6945248     0.23   0.822    -1.204738    1.517749
            882  |  -.0905799    .602018    -0.15   0.880    -1.270513    1.089354
           1292  |   2.572833   .5262588     4.89   0.000     1.541385    3.604281
           1592  |   .4414614   .5483656     0.81   0.421    -.6333154    1.516238
           2217  |   1.192656   .3033502     3.93   0.000     .5981001    1.787211
           2670  |  -.6625481   .4539236    -1.46   0.144    -1.552222    .2271258
           2724  |  -.4316205     .54455    -0.79   0.428    -1.498919    .6356778
                 |
           _cons |  -.1206994   1.391609    -0.09   0.931    -2.848203    2.606804
----------------------------------------------------------------------------------

Predictive margins                                       Number of obs = 2,186
Model VCE: Robust

Expression: Pr(faces_any_fem), predict()
1._at: only_women = 0
2._at: only_women = 1

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   std. err.      z    P>|z|     [95% conf. interval]
-------------+----------------------------------------------------------------
         _at |
          1  |   .4451937   .0076566    58.15   0.000     .4301871    .4602003
          2  |    .356455   .2024749     1.76   0.078    -.0403885    .7532984
------------------------------------------------------------------------------
Conservative

Iteration 0:   log pseudolikelihood = -17.572647  
Iteration 1:   log pseudolikelihood = -11.516279  
Iteration 2:   log pseudolikelihood = -11.135222  
Iteration 3:   log pseudolikelihood = -11.125083  
Iteration 4:   log pseudolikelihood = -11.125042  
Iteration 5:   log pseudolikelihood = -11.125042  

Logistic regression                                     Number of obs =  9,273
                                                        Wald chi2(2)  =      .
                                                        Prob > chi2   =      .
Log pseudolikelihood = -11.125042                       Pseudo R2     = 0.3669

                                (Std. err. adjusted for 29 clusters in parlgov_id)
----------------------------------------------------------------------------------
                 |               Robust
   faces_any_fem | Coefficient  std. err.      z    P>|z|     [95% conf. interval]
-----------------+----------------------------------------------------------------
    1.only_women |   .1224002   .2549331     0.48   0.631    -.3772595      .62206
audience_avg_age |   .0144623   .0098393     1.47   0.142    -.0048224     .033747
          nfaces |   1.416944   .2631966     5.38   0.000     .9010881      1.9328
                 |
      parlgov_id |
            280  |   2.766373   .3953273     7.00   0.000     1.991546      3.5412
            363  |   1.820288   .2814391     6.47   0.000     1.268678    2.371898
            417  |   1.659619   .2884326     5.75   0.000     1.094302    2.224937
            437  |   .5735978   .3601254     1.59   0.111    -.1322349    1.279431
            438  |   3.258311   .3217507    10.13   0.000     2.627691    3.888931
            501  |   1.474399   .2550668     5.78   0.000     .9744773    1.974321
            512  |   1.975516   .4976921     3.97   0.000     1.000057    2.950975
            528  |   3.691013   .5190235     7.11   0.000     2.673746     4.70828
            590  |   1.368203   .3363458     4.07   0.000     .7089774    2.027429
            596  |   .0180755   .3635114     0.05   0.960    -.6943938    .7305447
            645  |   .8091592   .4257871     1.90   0.057    -.0253682    1.643687
            657  |   1.453558   .3753592     3.87   0.000      .717867    2.189248
            773  |   3.376919   .4302138     7.85   0.000     2.533715    4.220122
            829  |   1.229751   .2623775     4.69   0.000     .7155002    1.744001
            851  |  -.2620862   .2688464    -0.97   0.330    -.7890154    .2648431
            984  |    3.09782   .3277218     9.45   0.000     2.455497    3.740143
           1045  |   2.557683    .281152     9.10   0.000     2.006635     3.10873
           1118  |  -.0836168   .4645702    -0.18   0.857    -.9941576     .826924
           1421  |   1.572104   .2953744     5.32   0.000     .9931805    2.151027
           1575  |   1.668765   .2887659     5.78   0.000     1.102795    2.234736
           1582  |   3.471445   .3278029    10.59   0.000     2.828963    4.113926
           1597  |   .4818893   .3068191     1.57   0.116    -.1194652    1.083244
           1620  |   1.133437   .4821816     2.35   0.019     .1883786    2.078496
           1666  |   1.072341    .235375     4.56   0.000      .611014    1.533667
           1759  |    1.99241   .2590005     7.69   0.000     1.484778    2.500042
           2154  |   7.586754   .3726866    20.36   0.000     6.856302    8.317207
           2659  |   2.745704   .3491364     7.86   0.000     2.061409    3.429999
           2717  |   .1052669   .2418371     0.44   0.663    -.3687251    .5792588
                 |
           _cons |  -4.919525   .5819184    -8.45   0.000    -6.060064   -3.778986
----------------------------------------------------------------------------------

Predictive margins                                       Number of obs = 9,273
Model VCE: Robust

Expression: Pr(faces_any_fem), predict()
1._at: only_women = 0
2._at: only_women = 1

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   std. err.      z    P>|z|     [95% conf. interval]
-------------+----------------------------------------------------------------
         _at |
          1  |   .2945557   .0008101   363.58   0.000     .2929679    .2961436
          2  |   .3096294   .0312113     9.92   0.000     .2484565    .3708024
------------------------------------------------------------------------------
Green_Ecologist

Iteration 0:   log pseudolikelihood = -9.6949693  
Iteration 1:   log pseudolikelihood = -6.5366083  
Iteration 2:   log pseudolikelihood = -6.2083235  
Iteration 3:   log pseudolikelihood = -6.1915801  
Iteration 4:   log pseudolikelihood = -6.1915393  
Iteration 5:   log pseudolikelihood = -6.1915393  

Logistic regression                                     Number of obs =  7,298
                                                        Wald chi2(2)  =      .
                                                        Prob > chi2   =      .
Log pseudolikelihood = -6.1915393                       Pseudo R2     = 0.3614

                                (Std. err. adjusted for 14 clusters in parlgov_id)
----------------------------------------------------------------------------------
                 |               Robust
   faces_any_fem | Coefficient  std. err.      z    P>|z|     [95% conf. interval]
-----------------+----------------------------------------------------------------
    1.only_women |   .1941891   .3021331     0.64   0.520    -.3979809    .7863591
audience_avg_age |  -.0226718   .0122595    -1.85   0.064    -.0466999    .0013563
          nfaces |   1.976438   .3225361     6.13   0.000     1.344279    2.608597
                 |
      parlgov_id |
            196  |   .0756356   .2237234     0.34   0.735    -.3628542    .5141255
            310  |   .2271759   .0753791     3.01   0.003     .0794357    .3749162
            360  |  -4.398855   .7335385    -6.00   0.000    -5.836564   -2.961146
            403  |  -.2386296   .1685235    -1.42   0.157    -.5689296    .0916704
            467  |  -.7114229   .2109441    -3.37   0.001    -1.124866     -.29798
            756  |  -.9057301    .140989    -6.42   0.000    -1.182063   -.6293968
            772  |  -.0793211   .0881404    -0.90   0.368    -.2520732     .093431
           1062  |   .5935888   .0702398     8.45   0.000     .4559213    .7312563
           1154  |   .7916533   .2035014     3.89   0.000     .3927979    1.190509
           1429  |  -1.474974   .1895277    -7.78   0.000    -1.846442   -1.103507
           1573  |   2.188411   .0703783    31.09   0.000     2.050472     2.32635
           1594  |  -.0425328   .1152493    -0.37   0.712    -.2684172    .1833517
           1644  |   1.479765    .125381    11.80   0.000     1.234023    1.725508
                 |
           _cons |  -.9586024   .4610316    -2.08   0.038    -1.862208    -.054997
----------------------------------------------------------------------------------

Predictive margins                                       Number of obs = 7,298
Model VCE: Robust

Expression: Pr(faces_any_fem), predict()
1._at: only_women = 0
2._at: only_women = 1

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   std. err.      z    P>|z|     [95% conf. interval]
-------------+----------------------------------------------------------------
         _at |
          1  |   .4795203   .0038566   124.34   0.000     .4719615     .487079
          2  |    .507595    .040126    12.65   0.000     .4289496    .5862405
------------------------------------------------------------------------------
Liberal

Iteration 0:   log pseudolikelihood = -12.484691  
Iteration 1:   log pseudolikelihood = -9.1833006  
Iteration 2:   log pseudolikelihood = -8.6427996  
Iteration 3:   log pseudolikelihood = -8.5954479  
Iteration 4:   log pseudolikelihood = -8.5928195  
Iteration 5:   log pseudolikelihood = -8.5927919  
Iteration 6:   log pseudolikelihood = -8.5927919  

Logistic regression                                     Number of obs = 14,986
                                                        Wald chi2(2)  =      .
                                                        Prob > chi2   =      .
Log pseudolikelihood = -8.5927919                       Pseudo R2     = 0.3117

                                (Std. err. adjusted for 21 clusters in parlgov_id)
----------------------------------------------------------------------------------
                 |               Robust
   faces_any_fem | Coefficient  std. err.      z    P>|z|     [95% conf. interval]
-----------------+----------------------------------------------------------------
    1.only_women |   .8696308   .6181161     1.41   0.159    -.3418545    2.081116
audience_avg_age |   -.014173   .0151103    -0.94   0.348    -.0437887    .0154427
          nfaces |   1.483207   .2405491     6.17   0.000     1.011739    1.954675
                 |
      parlgov_id |
            345  |   2.329476   .2911982     8.00   0.000     1.758738    2.900214
            376  |   1.167559   .2947064     3.96   0.000     .5899451    1.745173
            543  |   1.646353    .202777     8.12   0.000     1.248918    2.043789
            581  |   1.691022   .2450611     6.90   0.000     1.210711    2.171333
            585  |   2.410345    .259167     9.30   0.000     1.902387    2.918303
            659  |  -.2014201   .2237027    -0.90   0.368    -.6398694    .2370291
            892  |   1.605655   .2650666     6.06   0.000     1.086134    2.125176
            915  |   2.194393   .4091801     5.36   0.000     1.392415    2.996371
            967  |   2.843838   .2866317     9.92   0.000      2.28205    3.405626
            969  |   .8354122   .2523619     3.31   0.001     .3407919    1.330033
           1015  |   .4619153   .2320934     1.99   0.047     .0070205    .9168101
           1110  |    2.52162   .2386506    10.57   0.000     2.053873    2.989366
           1384  |   -3.76521   .7695873    -4.89   0.000    -5.273573   -2.256846
           1409  |   .5477191   .2693666     2.03   0.042     .0197703    1.075668
           1605  |   1.068896   .2315048     4.62   0.000     .6151551    1.522637
           2255  |   1.802213    .353331     5.10   0.000     1.109697    2.494729
           2263  |   3.122225   .2785326    11.21   0.000     2.576311    3.668138
           2375  |   .1017493   .2201035     0.46   0.644    -.3296456    .5331443
           2647  |  -.3655823   .1686308    -2.17   0.030    -.6960925   -.0350721
           2751  |  -1.663918   .5290234    -3.15   0.002    -2.700785   -.6270512
                 |
           _cons |  -3.283884   .7647991    -4.29   0.000    -4.782862   -1.784905
----------------------------------------------------------------------------------
Note: 0 failures and 33 successes completely determined.

Predictive margins                                      Number of obs = 14,986
Model VCE: Robust

Expression: Pr(faces_any_fem), predict()
1._at: only_women = 0
2._at: only_women = 1

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   std. err.      z    P>|z|     [95% conf. interval]
-------------+----------------------------------------------------------------
         _at |
          1  |   .2760499   .0041394    66.69   0.000     .2679369    .2841629
          2  |   .4000588   .0871684     4.59   0.000     .2292119    .5709057
------------------------------------------------------------------------------
Social_democracy

Iteration 0:   log pseudolikelihood = -21.721699  
Iteration 1:   log pseudolikelihood = -17.425695  
Iteration 2:   log pseudolikelihood = -16.917817  
Iteration 3:   log pseudolikelihood = -16.886143  
Iteration 4:   log pseudolikelihood = -16.885331  
Iteration 5:   log pseudolikelihood = -16.885328  
Iteration 6:   log pseudolikelihood = -16.885328  

Logistic regression                                     Number of obs = 15,036
                                                        Wald chi2(2)  =      .
                                                        Prob > chi2   =      .
Log pseudolikelihood = -16.885328                       Pseudo R2     = 0.2227

                                (Std. err. adjusted for 32 clusters in parlgov_id)
----------------------------------------------------------------------------------
                 |               Robust
   faces_any_fem | Coefficient  std. err.      z    P>|z|     [95% conf. interval]
-----------------+----------------------------------------------------------------
    1.only_women |   1.075074   .3400852     3.16   0.002      .408519    1.741629
audience_avg_age |   .0007011   .0072042     0.10   0.922    -.0134189    .0148212
          nfaces |   .8576664   .2996771     2.86   0.004     .2703101    1.445023
                 |
      parlgov_id |
            318  |   2.285357   .2129711    10.73   0.000     1.867941    2.702772
            382  |   .7695247   .0771985     9.97   0.000     .6182185     .920831
            395  |   2.590218   .0590459    43.87   0.000      2.47449    2.705946
            558  |   .8181814   .2620838     3.12   0.002     .3045066    1.331856
            701  |   1.118988   .1062039    10.54   0.000     .9108326    1.327144
            706  |   1.629539   .1139586    14.30   0.000     1.406185    1.852894
            742  |   .5977814   .0570267    10.48   0.000     .4860111    .7095517
            789  |   .9150272   .0429249    21.32   0.000      .830896    .9991584
            902  |    1.80157   .2112976     8.53   0.000     1.387434    2.215705
            904  |   .5749547   .2059548     2.79   0.005     .1712907    .9786188
            945  |   1.292376   .1271629    10.16   0.000     1.043141    1.541611
            973  |   1.068188   .1681284     6.35   0.000      .738662    1.397713
           1029  |   1.592075   .1041261    15.29   0.000     1.387991    1.796158
           1120  |   1.757455   .1615047    10.88   0.000     1.440912    2.073999
           1137  |    1.53058   .1262805    12.12   0.000     1.283075    1.778085
           1284  |    1.99181   .3562724     5.59   0.000     1.293529    2.690091
           1338  |   1.676601   .2400153     6.99   0.000      1.20618    2.147023
           1378  |    .917713   .1016203     9.03   0.000     .7185408    1.116885
           1448  |   2.935276   .0655532    44.78   0.000     2.806794    3.063758
           1493  |   2.276229   .1387583    16.40   0.000     2.004268    2.548191
           1520  |  -3.194374   1.288498    -2.48   0.013    -5.719784   -.6689631
           1556  |   .0595588   .1359868     0.44   0.661    -.2069705     .326088
           1591  |   .2075026   .0716251     2.90   0.004     .0671201    .3478851
           1629  |   2.604737   .0890316    29.26   0.000     2.430238    2.779236
           1970  |   2.850533   .1198703    23.78   0.000     2.615591    3.085474
           2337  |    1.81768   .0858413    21.17   0.000     1.649434    1.985926
           2341  |  -1.249541   .7002182    -1.78   0.074    -2.621944    .1228613
           2346  |   2.327511   .1074955    21.65   0.000     2.116823    2.538198
           2625  |   1.426012   .0827802    17.23   0.000     1.263765    1.588258
           2668  |    1.72344   .0669175    25.75   0.000     1.592284    1.854596
           2740  |    .870868    .123675     7.04   0.000     .6284695    1.113267
                 |
           _cons |  -2.747919   .4901008    -5.61   0.000    -3.708498   -1.787339
----------------------------------------------------------------------------------
Note: 0 failures and 8 successes completely determined.

Predictive margins                                      Number of obs = 15,036
Model VCE: Robust

Expression: Pr(faces_any_fem), predict()
1._at: only_women = 0
2._at: only_women = 1

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   std. err.      z    P>|z|     [95% conf. interval]
-------------+----------------------------------------------------------------
         _at |
          1  |   .4021434   .0041028    98.02   0.000     .3941021    .4101847
          2  |   .5985053   .0575176    10.41   0.000     .4857729    .7112378
------------------------------------------------------------------------------

. 
. 
. 
. * ##############################################################################
. * Robustness
. * ##############################################################################
. 
. 
. *****************************
. * 2 - DV: Any woman on image, Images only, Controls: Audience age, number of faces
. *****************************
. 
. * Add number of ads per party
. quietly logit faces_any_fem i.only_women c.audience_avg_age c.nfaces i.parlgov_id if is_img == 1  // Quietly ru
> n model to use same observations 

. cap drop n_ads

. bysort parlgov_id: gen n_ads=_N if e(sample)
(35,890 missing values generated)

. 
. * Run regression 
. logit faces_any_fem i.only_women c.audience_avg_age c.nfaces i.parlgov_id [iweight=1/n_ads] if is_img == 1, clu
> ster(parlgov_id)

Iteration 0:   log pseudolikelihood = -42.541695  
Iteration 1:   log pseudolikelihood = -26.246383  
Iteration 2:   log pseudolikelihood = -23.813525  
Iteration 3:   log pseudolikelihood = -23.217417  
Iteration 4:   log pseudolikelihood = -23.196823  
Iteration 5:   log pseudolikelihood = -23.196241  
Iteration 6:   log pseudolikelihood = -23.196232  
Iteration 7:   log pseudolikelihood = -23.196232  

Logistic regression                                     Number of obs = 26,882
                                                        Wald chi2(25) =      .
                                                        Prob > chi2   =      .
Log pseudolikelihood = -23.196232                       Pseudo R2     = 0.4547

                               (Std. err. adjusted for 121 clusters in parlgov_id)
----------------------------------------------------------------------------------
                 |               Robust
   faces_any_fem | Coefficient  std. err.      z    P>|z|     [95% conf. interval]
-----------------+----------------------------------------------------------------
    1.only_women |    1.03975   .2714799     3.83   0.000     .5076589     1.57184
audience_avg_age |   .0025139   .0060489     0.42   0.678    -.0093416    .0143695
          nfaces |   1.568462   .1726709     9.08   0.000     1.230033    1.906891
                 |
      parlgov_id |
             50  |   2.244427   .3116723     7.20   0.000      1.63356    2.855293
            118  |   2.021872   .2618542     7.72   0.000     1.508647    2.535097
            196  |   6.853073   .6174553    11.10   0.000     5.642882    8.063263
            256  |   .6018299   .0851116     7.07   0.000     .4350143    .7686456
            276  |   6.317308   .6605578     9.56   0.000     5.022639    7.611978
            280  |   5.695394   .6412338     8.88   0.000     4.438599    6.952189
            282  |   7.211673   .6879454    10.48   0.000     5.863324    8.560021
            306  |   6.342814   .7039957     9.01   0.000     4.963008    7.722621
            310  |   6.168861   .6994303     8.82   0.000     4.798002    7.539719
            311  |   6.428871   .7490848     8.58   0.000     4.960692    7.897051
            345  |   5.911608   .6478091     9.13   0.000     4.641925     7.18129
            357  |   6.873395   .7295872     9.42   0.000      5.44343    8.303359
            360  |  -.2092024   .1641182    -1.27   0.202    -.5308681    .1124632
            363  |   4.450093   .5720285     7.78   0.000     3.328938    5.571249
            376  |   7.641315   .5991474    12.75   0.000     6.467008    8.815623
            382  |   4.990496    .547181     9.12   0.000     3.918041    6.062951
            395  |   6.821573    .653392    10.44   0.000     5.540948    8.102197
            403  |   5.604213   .5980434     9.37   0.000      4.43207    6.776357
            437  |   3.567476    .644767     5.53   0.000     2.303755    4.831196
            438  |  -.1348991   .1481738    -0.91   0.363    -.4253143    .1555161
            457  |   7.517207    .696741    10.79   0.000      6.15162    8.882794
            467  |   2.878296   .4714399     6.11   0.000     1.954291    3.802301
            501  |   5.479539   .6173352     8.88   0.000     4.269585    6.689494
            512  |   5.116836   .7803631     6.56   0.000     3.587352    6.646319
            528  |   5.442715   .6284852     8.66   0.000     4.210906    6.674523
            543  |   6.200642   .7275631     8.52   0.000     4.774644    7.626639
            558  |   6.163419   .7121859     8.65   0.000      4.76756    7.559277
            572  |   5.422465   .6492498     8.35   0.000     4.149959    6.694971
            581  |   6.399962   .6865814     9.32   0.000     5.054287    7.745637
            585  |   6.644821   .7060012     9.41   0.000     5.261084    8.028558
            590  |    4.42516   .5775303     7.66   0.000     3.293221    5.557098
            600  |  -1.765658    .297008    -5.94   0.000    -2.347783   -1.183533
            645  |    4.04212   .6902936     5.86   0.000      2.68917    5.395071
            657  |   5.488137   .6810235     8.06   0.000     4.153356    6.822919
            659  |   2.127884   .4479211     4.75   0.000     1.249975    3.005794
            701  |    4.57986    .543623     8.42   0.000     3.514378    5.645341
            706  |   5.113708    .595784     8.58   0.000     3.945993    6.281423
            723  |   6.166499   .6503508     9.48   0.000     4.891834    7.441163
            742  |   2.687034   .3702796     7.26   0.000       1.9613    3.412769
            756  |   5.386817   .6693545     8.05   0.000     4.074906    6.698728
            757  |   5.125435   .5575427     9.19   0.000     4.032671    6.218198
            772  |    5.92627    .663046     8.94   0.000     4.626724    7.225816
            773  |    3.99571   .5377312     7.43   0.000     2.941776    5.049644
            789  |   6.046568   .6592952     9.17   0.000     4.754373    7.338762
            791  |   5.034624   .7063778     7.13   0.000     3.650148    6.419099
            829  |   4.866165   .5674462     8.58   0.000     3.753991    5.978339
            851  |   .3379226   .1205427     2.80   0.005     .1016633    .5741819
            865  |   5.178056   .6879494     7.53   0.000       3.8297    6.526412
            882  |   5.766771   .6649283     8.67   0.000     4.463535    7.070006
            892  |   5.437245   .6140853     8.85   0.000      4.23366     6.64083
            904  |   5.737357    .688519     8.33   0.000     4.387885     7.08683
            915  |   5.356805   .6009214     8.91   0.000      4.17902    6.534589
            945  |   6.524715   .6632675     9.84   0.000     5.224734    7.824695
            967  |   6.583526   .6349091    10.37   0.000     5.339127    7.827925
            969  |   5.505951   .7149883     7.70   0.000       4.1046    6.907302
            973  |   6.325519   .7142587     8.86   0.000     4.925598    7.725441
            984  |   6.622812   .6345718    10.44   0.000     5.379074     7.86655
            990  |   5.289237    .793656     6.66   0.000       3.7337    6.844774
            993  |   3.908897    .474347     8.24   0.000     2.979194      4.8386
           1013  |    -.17422   .4054692    -0.43   0.667    -.9689251     .620485
           1015  |   4.099363   .5760244     7.12   0.000     2.970376     5.22835
           1029  |   6.651644   .6683861     9.95   0.000     5.341631    7.961656
           1045  |   5.949432   .5814907    10.23   0.000     4.809731    7.089132
           1062  |   5.501038    .429099    12.82   0.000     4.660019    6.342056
           1072  |   4.408765   .5101879     8.64   0.000     3.408815    5.408715
           1110  |   5.708113   .5927189     9.63   0.000     4.546405    6.869821
           1118  |   6.876169   .6870295    10.01   0.000     5.529616    8.222722
           1120  |   5.528689   .6591414     8.39   0.000     4.236796    6.820583
           1137  |   6.078231   .6233315     9.75   0.000     4.856523    7.299938
           1154  |   7.846607   .5964698    13.16   0.000     6.677548    9.015667
           1192  |   6.674327   .6872146     9.71   0.000     5.327411    8.021243
           1206  |   5.621655   .7259711     7.74   0.000     4.198778    7.044532
           1234  |   5.559563   .6558551     8.48   0.000     4.274111    6.845015
           1245  |   5.640887   .6496618     8.68   0.000     4.367574    6.914201
           1292  |   8.409845   .6038367    13.93   0.000     7.226346    9.593343
           1378  |   4.631985   .5544335     8.35   0.000     3.545316    5.718655
           1418  |   5.231573   .4993654    10.48   0.000     4.252835    6.210311
           1421  |   5.400494   .6259418     8.63   0.000     4.173671    6.627317
           1429  |   4.297451   .5487812     7.83   0.000      3.22186    5.373042
           1432  |   .7425033   .1281074     5.80   0.000     .4914174    .9935892
           1448  |   7.915453   .6454411    12.26   0.000     6.650412    9.180495
           1461  |   7.959729   .6935642    11.48   0.000     6.600369     9.31909
           1463  |  -8.254768   1.860726    -4.44   0.000    -11.90172   -4.607812
           1465  |   3.033219    .331518     9.15   0.000     2.383456    3.682983
           1493  |  -3.033866   .4937596    -6.14   0.000    -4.001617   -2.066115
           1521  |   6.097108   .6478206     9.41   0.000     4.827403    7.366813
           1546  |   4.524496   .6498496     6.96   0.000     3.250814    5.798178
           1556  |   1.623088   .2764489     5.87   0.000     1.081258    2.164918
           1575  |   4.267599    .485151     8.80   0.000     3.316721    5.218478
           1591  |   4.503053   .5516383     8.16   0.000     3.421862    5.584244
           1594  |   6.227478   .6350004     9.81   0.000       4.9829    7.472056
           1597  |   3.725923   .6499767     5.73   0.000     2.451993    4.999854
           1605  |   4.898626   .5937816     8.25   0.000     3.734836    6.062417
           1629  |   7.760309   .6682007    11.61   0.000     6.450659    9.069958
           1644  |    6.94163   .6666852    10.41   0.000     5.634951    8.248309
           1666  |   3.734851    .467758     7.98   0.000     2.818062     4.65164
           1727  |   5.039206   .6178899     8.16   0.000     3.828164    6.250248
           1759  |   3.573439   .3628272     9.85   0.000     2.862311    4.284567
           1970  |   7.952128   .7147824    11.13   0.000      6.55118    9.353076
           2154  |   11.49847   .6664484    17.25   0.000     10.19225    12.80468
           2255  |   5.860488   .5931837     9.88   0.000      4.69787    7.023107
           2256  |   2.267906   .2745144     8.26   0.000     1.729868    2.805944
           2261  |   4.397921   .6923602     6.35   0.000      3.04092    5.754923
           2337  |    6.37578    .561146    11.36   0.000     5.275954    7.475606
           2341  |  -1.588778   .2478425    -6.41   0.000     -2.07454   -1.103015
           2375  |   1.931504   .2393331     8.07   0.000      1.46242    2.400589
           2395  |   4.122873   .4611286     8.94   0.000     3.219078    5.026669
           2600  |   4.015337   .5574036     7.20   0.000     2.922846    5.107828
           2625  |   6.124462   .6640097     9.22   0.000     4.823027    7.425897
           2647  |   4.543747   .6334212     7.17   0.000     3.302264    5.785229
           2659  |   6.864841   .6557898    10.47   0.000     5.579517    8.150165
           2668  |   7.070144   .6957793    10.16   0.000     5.706441    8.433846
           2670  |   4.643382   .6797701     6.83   0.000     3.311057    5.975707
           2717  |   3.744268   .5166894     7.25   0.000     2.731576    4.756961
           2724  |   4.189768   .6272278     6.68   0.000     2.960424    5.419112
           2729  |   5.381878   .6213405     8.66   0.000     4.164073    6.599683
           2730  |   4.094723   .6899106     5.94   0.000     2.742523    5.446923
           2740  |   6.447365   .6187882    10.42   0.000     5.234562    7.660167
           2750  |   4.696532   .4600099    10.21   0.000     3.794929    5.598135
           2751  |   .6602591   .1236456     5.34   0.000     .4179183    .9025999
                 |
           _cons |  -8.576615   .7246541   -11.84   0.000    -9.996911   -7.156319
----------------------------------------------------------------------------------
Note: 0 failures and 132 successes completely determined.

. est store inter

. 
. * Run models for each party family
. levelsof pg_party_family_name if inlist(pg_party_family_name,  "Green_Ecologist","Communist_Socialist", "Social
> _democracy", "Christian_democracy", "Conservative", "Liberal", "Right_wing"), local(groups)
`"Christian_democracy"' `"Communist_Socialist"' `"Conservative"' `"Green_Ecologist"' `"Liberal"' `"Right_wing"' `
> "Social_democracy"'

. local estimates_list // 

. foreach g of local groups {
  2.         di "`g'"
  3.    logit faces_any_fem i.only_women c.audience_avg_age c.nfaces i.parlgov_id [iweight=1/n_ads] if is_img == 
> 1 & pg_party_family_name ==  "`g'", cluster(parlgov_id)
  4.         est store `g'   
  5. }
Christian_democracy

Iteration 0:   log pseudolikelihood =  -5.097994  
Iteration 1:   log pseudolikelihood = -2.6518607  
Iteration 2:   log pseudolikelihood = -2.1262913  
Iteration 3:   log pseudolikelihood = -1.9776611  
Iteration 4:   log pseudolikelihood =  -1.972366  
Iteration 5:   log pseudolikelihood = -1.9720478  
Iteration 6:   log pseudolikelihood = -1.9720314  
Iteration 7:   log pseudolikelihood = -1.9720314  

Logistic regression                                     Number of obs =  1,117
                                                        Wald chi2(4)  =      .
                                                        Prob > chi2   =      .
Log pseudolikelihood = -1.9720314                       Pseudo R2     = 0.6132

                                (Std. err. adjusted for 13 clusters in parlgov_id)
----------------------------------------------------------------------------------
                 |               Robust
   faces_any_fem | Coefficient  std. err.      z    P>|z|     [95% conf. interval]
-----------------+----------------------------------------------------------------
    1.only_women |   1.817027   .8112321     2.24   0.025     .2270414    3.407013
audience_avg_age |   .0015952   .0203611     0.08   0.938    -.0383118    .0415021
          nfaces |   2.411899    .881669     2.74   0.006     .6838598    4.139939
                 |
      parlgov_id |
            282  |   .8750714   .1611839     5.43   0.000     .5591567    1.190986
            723  |  -.2129883   .0620752    -3.43   0.001    -.3346534   -.0913232
           1013  |  -8.539788   1.845076    -4.63   0.000    -12.15607   -4.923506
           1192  |   .4566783    .119203     3.83   0.000     .2230447    .6903119
           1206  |  -.4143356    .191907    -2.16   0.031    -.7904665   -.0382047
           1234  |  -.7276685   .2042015    -3.56   0.000    -1.127896    -.327441
           1245  |  -1.211079   .5200809    -2.33   0.020    -2.230419   -.1917395
           1432  |  -8.583689   3.075558    -2.79   0.005    -14.61167   -2.555705
           1463  |  -27.14334          .        .       .            .           .
           1727  |  -1.434381   .3277242    -4.38   0.000    -2.076709   -.7920536
           2395  |  -3.348482   1.156205    -2.90   0.004    -5.614603   -1.082362
           2750  |  -2.552679   1.090957    -2.34   0.019    -4.690915   -.4144438
                 |
           _cons |  -2.985904   .4034387    -7.40   0.000    -3.776629   -2.195178
----------------------------------------------------------------------------------
Note: 1 failure and 3 successes completely determined.
Communist_Socialist

Iteration 0:   log pseudolikelihood = -2.8777547  
Iteration 1:   log pseudolikelihood = -1.9164875  
Iteration 2:   log pseudolikelihood = -1.8565458  
Iteration 3:   log pseudolikelihood = -1.8511814  
Iteration 4:   log pseudolikelihood = -1.8511657  
Iteration 5:   log pseudolikelihood = -1.8511657  

Logistic regression                                     Number of obs =    783
                                                        Wald chi2(2)  =      .
                                                        Prob > chi2   =      .
Log pseudolikelihood = -1.8511657                       Pseudo R2     = 0.3567

                                (Std. err. adjusted for 11 clusters in parlgov_id)
----------------------------------------------------------------------------------
                 |               Robust
   faces_any_fem | Coefficient  std. err.      z    P>|z|     [95% conf. interval]
-----------------+----------------------------------------------------------------
    1.only_women |   .1268236   .2117081     0.60   0.549    -.2881167    .5417638
audience_avg_age |  -.0064911   .0085638    -0.76   0.448    -.0232758    .0102936
          nfaces |   .9371004    .547999     1.71   0.087    -.1369579    2.011159
                 |
      parlgov_id |
            256  |  -.5618799   .7972455    -0.70   0.481    -2.124452    1.000693
            306  |   2.588537   1.398049     1.85   0.064    -.1515883    5.328662
            357  |   3.267057   1.365418     2.39   0.017      .590887    5.943227
            457  |   3.515913   1.445513     2.43   0.015     .6827607    6.349066
            572  |   1.906192   1.173733     1.62   0.104    -.3942813    4.206666
            791  |   1.172562   1.503479     0.78   0.435    -1.774203    4.119327
            882  |   2.516793   1.286957     1.96   0.051    -.0055974    5.039182
           1292  |   4.746371   1.148473     4.13   0.000     2.495406    6.997337
           2670  |   1.093582   1.249604     0.88   0.381    -1.355596     3.54276
           2724  |    .744737   1.146782     0.65   0.516    -1.502914    2.992388
                 |
           _cons |  -4.049385   1.660867    -2.44   0.015    -7.304624   -.7941461
----------------------------------------------------------------------------------
Conservative

Iteration 0:   log pseudolikelihood = -7.9406896  
Iteration 1:   log pseudolikelihood = -4.2999543  
Iteration 2:   log pseudolikelihood = -3.9985894  
Iteration 3:   log pseudolikelihood = -3.9700426  
Iteration 4:   log pseudolikelihood = -3.9685837  
Iteration 5:   log pseudolikelihood = -3.9685712  
Iteration 6:   log pseudolikelihood = -3.9685711  

Logistic regression                                     Number of obs =  4,361
                                                        Wald chi2(2)  =      .
                                                        Prob > chi2   =      .
Log pseudolikelihood = -3.9685711                       Pseudo R2     = 0.5002

                                (Std. err. adjusted for 25 clusters in parlgov_id)
----------------------------------------------------------------------------------
                 |               Robust
   faces_any_fem | Coefficient  std. err.      z    P>|z|     [95% conf. interval]
-----------------+----------------------------------------------------------------
    1.only_women |   .6982791   .4531279     1.54   0.123    -.1898352    1.586393
audience_avg_age |   .0098876   .0135457     0.73   0.465    -.0166615    .0364367
          nfaces |   1.427457    .312727     4.56   0.000     .8145235    2.040391
                 |
      parlgov_id |
            280  |   5.162061   1.120815     4.61   0.000     2.965304    7.358817
            363  |   3.915432   1.036409     3.78   0.000     1.884108    5.946756
            437  |   2.931065    1.18647     2.47   0.013      .605627    5.256503
            438  |  -.1352107   .3252848    -0.42   0.678    -.7727571    .5023357
            501  |   4.916069   1.104955     4.45   0.000     2.750397     7.08174
            512  |   4.389604    1.42039     3.09   0.002     1.605691    7.173517
            528  |   4.878386   1.139135     4.28   0.000     2.645722     7.11105
            590  |   3.884415   1.049029     3.70   0.000     1.828356    5.940475
            645  |     3.6166   1.227432     2.95   0.003     1.210878    6.022323
            657  |   4.834403   1.244993     3.88   0.000      2.39426    7.274545
            773  |   3.481607   .9845417     3.54   0.000      1.55194    5.411273
            829  |   4.342012   1.005896     4.32   0.000     2.370493    6.313531
            851  |   .1917688   .2738076     0.70   0.484    -.3448842    .7284218
            984  |   6.035119   1.138281     5.30   0.000     3.804129    8.266109
           1045  |   5.401837   1.040772     5.19   0.000     3.361961    7.441712
           1118  |   6.243599   1.241034     5.03   0.000     3.811217    8.675981
           1421  |   4.852425   1.110324     4.37   0.000     2.676229     7.02862
           1575  |   3.844301     .87608     4.39   0.000     2.127216    5.561387
           1597  |   3.120723   1.171089     2.66   0.008     .8254296    5.416016
           1666  |   3.310203    .837719     3.95   0.000     1.668304    4.952102
           1759  |   3.232067   .6766284     4.78   0.000       1.9059    4.558235
           2154  |   10.85866   1.208314     8.99   0.000     8.490411    13.22692
           2659  |   6.236014   1.183751     5.27   0.000     3.915905    8.556123
           2717  |   3.240522   .9555944     3.39   0.001     1.367591    5.113452
                 |
           _cons |  -8.137688   1.238853    -6.57   0.000    -10.56579   -5.709581
----------------------------------------------------------------------------------
Green_Ecologist

Iteration 0:   log pseudolikelihood =   -4.06029  
Iteration 1:   log pseudolikelihood =  -2.314571  
Iteration 2:   log pseudolikelihood = -2.0665517  
Iteration 3:   log pseudolikelihood = -2.0039826  
Iteration 4:   log pseudolikelihood = -2.0017654  
Iteration 5:   log pseudolikelihood = -2.0017461  
Iteration 6:   log pseudolikelihood = -2.0017461  

Logistic regression                                     Number of obs =  2,336
                                                        Wald chi2(2)  =      .
                                                        Prob > chi2   =      .
Log pseudolikelihood = -2.0017461                       Pseudo R2     = 0.5070

                                (Std. err. adjusted for 12 clusters in parlgov_id)
----------------------------------------------------------------------------------
                 |               Robust
   faces_any_fem | Coefficient  std. err.      z    P>|z|     [95% conf. interval]
-----------------+----------------------------------------------------------------
    1.only_women |   1.119586    .707114     1.58   0.113    -.2663321    2.505504
audience_avg_age |  -.0614829   .0304264    -2.02   0.043    -.1211176   -.0018481
          nfaces |   2.054862   .3434434     5.98   0.000     1.381726    2.727999
                 |
      parlgov_id |
            310  |  -.9296916   .2561437    -3.63   0.000    -1.431724   -.4276591
            360  |  -8.425742   1.404491    -6.00   0.000    -11.17849    -5.67299
            403  |  -1.157972    .144789    -8.00   0.000    -1.441753    -.874191
            467  |  -4.503319   .4061978   -11.09   0.000    -5.299452   -3.707186
            756  |  -1.527211   .1704929    -8.96   0.000    -1.861371   -1.193051
            772  |  -.8802309    .063049   -13.96   0.000    -1.003805   -.7566572
           1062  |  -2.063152   .5230792    -3.94   0.000    -3.088368   -1.037935
           1154  |   .2921224   .3330842     0.88   0.380    -.3607106    .9449554
           1429  |   -3.38384   .4019568    -8.42   0.000     -4.17166   -2.596019
           1594  |  -.6066332   .1284863    -4.72   0.000    -.8584617   -.3548048
           1644  |   .6798402   .2942065     2.31   0.021     .1032059    1.256474
                 |
           _cons |   .1299609   1.021591     0.13   0.899     -1.87232    2.132242
----------------------------------------------------------------------------------
Liberal

Iteration 0:   log pseudolikelihood = -4.9986497  
Iteration 1:   log pseudolikelihood = -3.6560845  
Iteration 2:   log pseudolikelihood = -3.4645581  
Iteration 3:   log pseudolikelihood =  -3.459851  
Iteration 4:   log pseudolikelihood = -3.4557059  (backed up)
Iteration 5:   log pseudolikelihood = -3.4451158  
Iteration 6:   log pseudolikelihood = -3.4395103  
Iteration 7:   log pseudolikelihood = -3.4350454  
Iteration 8:   log pseudolikelihood = -3.4350205  
Iteration 9:   log pseudolikelihood = -3.4350204  

Logistic regression                                     Number of obs =  6,642
                                                        Wald chi2(2)  =      .
                                                        Prob > chi2   =      .
Log pseudolikelihood = -3.4350204                       Pseudo R2     = 0.3128

                                (Std. err. adjusted for 17 clusters in parlgov_id)
----------------------------------------------------------------------------------
                 |               Robust
   faces_any_fem | Coefficient  std. err.      z    P>|z|     [95% conf. interval]
-----------------+----------------------------------------------------------------
    1.only_women |   .4290117   .3691466     1.16   0.245    -.2945023    1.152526
audience_avg_age |   .0014372   .0200522     0.07   0.943    -.0378644    .0407388
          nfaces |   1.412724   .3851066     3.67   0.000     .6579286    2.167519
                 |
      parlgov_id |
            376  |   1.728678   .2709918     6.38   0.000     1.197544    2.259812
            543  |   .5022008   .2599113     1.93   0.053    -.0072161    1.011618
            581  |    .503608   .2466912     2.04   0.041     .0201022    .9871138
            585  |   .7182632   .2353288     3.05   0.002     .2570273    1.179499
            659  |   -3.24407   .3875149    -8.37   0.000    -4.003585   -2.484555
            892  |  -.4269913   .0928762    -4.60   0.000    -.6090253   -.2449573
            915  |  -.5068032   .0956232    -5.30   0.000    -.6942213   -.3193852
            967  |   .6716126    .071773     9.36   0.000     .5309401     .812285
            969  |  -.4328599   .2446735    -1.77   0.077    -.9124113    .0466914
           1015  |  -1.681849   .2350154    -7.16   0.000    -2.142471   -1.221228
           1110  |  -.1155792   .1573581    -0.73   0.463    -.4239953    .1928369
           1605  |   -.885578   .1876112    -4.72   0.000    -1.253289   -.5178669
           2255  |  -.0369445   .2164129    -0.17   0.864    -.4611061    .3872171
           2375  |  -3.546682   .9278197    -3.82   0.000    -5.365175   -1.728188
           2647  |  -1.322969   .1418885    -9.32   0.000    -1.601065   -1.044873
           2751  |  -4.746726   1.179275    -4.03   0.000    -7.058063    -2.43539
                 |
           _cons |  -2.482575   .6228217    -3.99   0.000    -3.703283   -1.261866
----------------------------------------------------------------------------------
Note: 0 failures and 26 successes completely determined.
Right_wing

note: 0.only_women != 1 predicts failure perfectly;
      0.only_women omitted and 1 obs not used.

note: 1.only_women omitted because of collinearity.
Iteration 0:   log pseudolikelihood = -2.1359849  
Iteration 1:   log pseudolikelihood = -1.1116251  
Iteration 2:   log pseudolikelihood = -.93480574  
Iteration 3:   log pseudolikelihood = -.90019652  
Iteration 4:   log pseudolikelihood = -.89910909  
Iteration 5:   log pseudolikelihood = -.89910545  
Iteration 6:   log pseudolikelihood = -.89910545  

Logistic regression                                     Number of obs =    545
                                                        Wald chi2(1)  =      .
                                                        Prob > chi2   =      .
Log pseudolikelihood = -.89910545                       Pseudo R2     = 0.5791

                                 (Std. err. adjusted for 7 clusters in parlgov_id)
----------------------------------------------------------------------------------
                 |               Robust
   faces_any_fem | Coefficient  std. err.      z    P>|z|     [95% conf. interval]
-----------------+----------------------------------------------------------------
    1.only_women |          0  (empty)
audience_avg_age |   .0281725   .0261329     1.08   0.281    -.0230471     .079392
          nfaces |    1.73546   .5283321     3.28   0.001     .6999476    2.770971
                 |
      parlgov_id |
            600  |   -4.60717    1.82461    -2.53   0.012     -8.18334      -1.031
            993  |   1.749847   .4811606     3.64   0.000     .8067894    2.692904
           1072  |   2.244912   .6417129     3.50   0.000     .9871779    3.502646
           1418  |   2.854415   .5930856     4.81   0.000     1.691988    4.016841
           1546  |   2.303695   1.088238     2.12   0.034     .1707879    4.436602
           2600  |   2.002121   .8351384     2.40   0.017       .36528    3.638962
                 |
           _cons |   -7.73829   1.593005    -4.86   0.000    -10.86052   -4.616057
----------------------------------------------------------------------------------
Note: 0 failures and 1 success completely determined.
Social_democracy

Iteration 0:   log pseudolikelihood = -10.820496  
Iteration 1:   log pseudolikelihood = -7.6147564  
Iteration 2:   log pseudolikelihood = -6.8753522  
Iteration 3:   log pseudolikelihood = -6.7282276  
Iteration 4:   log pseudolikelihood = -6.7264619  
Iteration 5:   log pseudolikelihood = -6.7264461  
Iteration 6:   log pseudolikelihood =  -6.726446  

Logistic regression                                     Number of obs = 10,003
                                                        Wald chi2(2)  =      .
                                                        Prob > chi2   =      .
Log pseudolikelihood = -6.726446                        Pseudo R2     = 0.3784

                                (Std. err. adjusted for 25 clusters in parlgov_id)
----------------------------------------------------------------------------------
                 |               Robust
   faces_any_fem | Coefficient  std. err.      z    P>|z|     [95% conf. interval]
-----------------+----------------------------------------------------------------
    1.only_women |   1.102736   .4020241     2.74   0.006     .3147836    1.890689
audience_avg_age |   .0032769   .0050999     0.64   0.521    -.0067187    .0132725
          nfaces |   1.548851   .4111735     3.77   0.000      .742966    2.354737
                 |
      parlgov_id |
            395  |   1.816872   .2222648     8.17   0.000     1.381241    2.252503
            558  |    1.12061    .432887     2.59   0.010     .2721673    1.969053
            701  |  -.4101667   .0051224   -80.07   0.000    -.4202065    -.400127
            706  |   .1168827   .1078058     1.08   0.278    -.0944127    .3281781
            742  |  -2.285297   .5047549    -4.53   0.000    -3.274599   -1.295996
            789  |   1.028695   .2559661     4.02   0.000     .5270106    1.530379
            904  |    .689599   .3799267     1.82   0.070    -.0550436    1.434242
            945  |   1.521472   .2903491     5.24   0.000     .9523984    2.090546
            973  |   1.310115   .3943592     3.32   0.001     .5371848    2.083044
           1029  |   1.647109   .2907517     5.67   0.000     1.077247    2.216972
           1120  |   .5218927   .2582595     2.02   0.043     .0157133    1.028072
           1137  |   1.082522   .2380051     4.55   0.000     .6160406    1.549003
           1378  |  -.3631882   .0252088   -14.41   0.000    -.4125965   -.3137799
           1448  |   2.903722   .2475624    11.73   0.000     2.418509    3.388935
           1493  |  -7.922456   2.442391    -3.24   0.001    -12.70945   -3.135458
           1556  |  -3.335812   .6775081    -4.92   0.000    -4.663703    -2.00792
           1591  |  -.4875743   .0201147   -24.24   0.000    -.5269984   -.4481501
           1629  |   2.754525   .2685353    10.26   0.000     2.228205    3.280844
           1970  |   2.938315   .3405561     8.63   0.000     2.270837    3.605792
           2337  |   1.382482   .0196404    70.39   0.000     1.343987    1.420977
           2341  |  -6.492805   1.831456    -3.55   0.000    -10.08239   -2.903217
           2625  |   1.105507   .2815332     3.93   0.000     .5537122    1.657302
           2668  |   2.060939   .3323825     6.20   0.000     1.409481    2.712397
           2740  |   1.445691   .2342341     6.17   0.000     .9866003    1.904781
                 |
           _cons |  -3.586373   .6241857    -5.75   0.000    -4.809754   -2.362992
----------------------------------------------------------------------------------
Note: 0 failures and 96 successes completely determined.

. 
. * Output all models to latex table
. outreg2 [inter Green_Ecologist  Communist_Socialist Social_democracy Christian_democracy Conservative Liberal R
> ight_wing] using 2.xls, replace drop(i.parlgov_id) label excel tex alpha(0.001, 0.01, 0.05, 0.1) symbol(***, **
> , *, +)  dec(3) e(N_clust)
2.tex
2.xls
dir : seeout

. 
. 
. 
. *****************************
. * 3  DV: Any woman on image, Controls: Share of women in audience, audience age, number of faces
. *****************************
. 
. 
. * Add number of ads per party
. cap drop n_ads

. quietly logit faces_any_fem c.fem_audience c.audience_avg_age c.nfaces i.parlgov_id // Quietly run model to use
>  same observations 

. bysort parlgov_id: gen n_ads=_N if e(sample)
(90 missing values generated)

. 
. * Run regression 
. logit faces_any_fem c.fem_audience c.audience_avg_age c.nfaces i.parlgov_id [iweight=1/n_ads], cluster(parlgov_
> id) 

Iteration 0:   log pseudolikelihood = -97.717909  
Iteration 1:   log pseudolikelihood = -72.715346  
Iteration 2:   log pseudolikelihood = -68.710861  
Iteration 3:   log pseudolikelihood = -68.415051  
Iteration 4:   log pseudolikelihood = -68.390546  
Iteration 5:   log pseudolikelihood =  -68.39008  
Iteration 6:   log pseudolikelihood = -68.390079  

Logistic regression                                     Number of obs = 62,682
                                                        Wald chi2(2)  =      .
                                                        Prob > chi2   =      .
Log pseudolikelihood = -68.390079                       Pseudo R2     = 0.3001

                               (Std. err. adjusted for 151 clusters in parlgov_id)
----------------------------------------------------------------------------------
                 |               Robust
   faces_any_fem | Coefficient  std. err.      z    P>|z|     [95% conf. interval]
-----------------+----------------------------------------------------------------
    fem_audience |   .9437262   .2213514     4.26   0.000     .5098855    1.377567
audience_avg_age |  -.0037436   .0047247    -0.79   0.428     -.013004    .0055167
          nfaces |   1.218087   .1594349     7.64   0.000     .9056008    1.530574
                 |
      parlgov_id |
             47  |   1.600021   .2341096     6.83   0.000     1.141174    2.058867
             50  |   1.231078   .1377475     8.94   0.000     .9610979    1.501058
            113  |   .4703778   .2362891     1.99   0.047     .0072597     .933496
            118  |   1.947182    .181287    10.74   0.000     1.591866    2.302498
            161  |   2.499884   .2849149     8.77   0.000     1.941461    3.058307
            196  |   3.103699   .1891827    16.41   0.000     2.732908    3.474491
            200  |   2.115636   .2550151     8.30   0.000     1.615816    2.615457
            220  |   .9673661   .1833451     5.28   0.000     .6080164    1.326716
            235  |   3.163787   .2912094    10.86   0.000     2.593028    3.734547
            256  |   1.846682    .111032    16.63   0.000     1.629064    2.064301
            276  |   2.749186   .2320489    11.85   0.000     2.294378    3.203993
            280  |   2.565676   .2457683    10.44   0.000     2.083979    3.047373
            282  |   3.653541    .235071    15.54   0.000      3.19281    4.114271
            306  |   3.000688    .272891    11.00   0.000     2.465831    3.535544
            310  |   2.902911   .2653567    10.94   0.000     2.382822    3.423001
            311  |   1.504014   .2366103     6.36   0.000     1.040266    1.967761
            318  |   3.394492   .2634307    12.89   0.000     2.878177    3.910806
            345  |   2.752975   .2341993    11.75   0.000     2.293953    3.211997
            357  |   2.776792   .2684518    10.34   0.000     2.250636    3.302947
            360  |   .0327408   .0868305     0.38   0.706    -.1374439    .2029255
            363  |   1.975545   .1698507    11.63   0.000     1.642644    2.308446
            376  |   1.835288   .2294505     8.00   0.000     1.385573    2.285003
            382  |   1.637813    .152945    10.71   0.000     1.338046     1.93758
            395  |   3.484981   .1977242    17.63   0.000     3.097449    3.872513
            403  |   2.635261   .2140932    12.31   0.000     2.215646    3.054876
            417  |   1.486381   .1908278     7.79   0.000     1.112365    1.860396
            437  |   .6770973   .2151861     3.15   0.002     .2553403    1.098854
            438  |   3.318503   .1893935    17.52   0.000     2.947299    3.689708
            457  |   3.243288   .2204174    14.71   0.000     2.811278    3.675298
            467  |   2.389221    .187673    12.73   0.000     2.021388    2.757053
            501  |   1.453859   .1578281     9.21   0.000     1.144521    1.763196
            512  |   1.827515   .3064727     5.96   0.000      1.22684     2.42819
            520  |   1.245659   .1734881     7.18   0.000     .9056284    1.585689
            528  |   3.399027   .3213522    10.58   0.000     2.769189    4.028866
            543  |   2.337401   .2729299     8.56   0.000     1.802468    2.872333
            558  |   2.404628   .2725428     8.82   0.000     1.870454    2.938802
            572  |   2.319335   .2334988     9.93   0.000     1.861685    2.776984
            581  |   1.973677     .23526     8.39   0.000     1.512576    2.434778
            585  |   2.590552   .2725851     9.50   0.000     2.056295    3.124809
            590  |   1.375816   .2014522     6.83   0.000     .9809772    1.770655
            596  |   .1144639   .2240564     0.51   0.609    -.3246786    .5536064
            600  |   .2359698   .1072293     2.20   0.028     .0258041    .4461354
            645  |   .6379202   .2598138     2.46   0.014     .1286945    1.147146
            657  |   1.635022   .2193237     7.45   0.000     1.205155    2.064888
            659  |   .6059249   .2310123     2.62   0.009      .153149    1.058701
            701  |   2.108829   .2110148     9.99   0.000     1.695248    2.522411
            706  |   2.725361   .2268368    12.01   0.000     2.280769    3.169953
            723  |   2.694235    .226166    11.91   0.000     2.250958    3.137512
            742  |   1.459888   .1645923     8.87   0.000     1.137293    1.782483
            756  |   1.920196   .2323328     8.26   0.000     1.464832    2.375559
            757  |   2.336679   .2157759    10.83   0.000     1.913766    2.759592
            772  |   2.646948   .2463408    10.75   0.000     2.164129    3.129767
            773  |   3.359423   .2597294    12.93   0.000     2.850363    3.868483
            789  |   2.009303   .1715985    11.71   0.000     1.672976     2.34563
            791  |   2.748989   .2684882    10.24   0.000     2.222762    3.275216
            829  |   1.244663   .1581896     7.87   0.000     .9346173    1.554709
            851  |   .0721595   .1437577     0.50   0.616    -.2096003    .3539194
            865  |   1.845547   .2584464     7.14   0.000     1.339001    2.352092
            882  |   1.946981   .2350851     8.28   0.000     1.486223    2.407739
            892  |   2.068224   .2241578     9.23   0.000     1.628883    2.507565
            902  |   2.843082   .2612759    10.88   0.000      2.33099    3.355173
            904  |   2.062103   .2283109     9.03   0.000     1.614622    2.509585
            915  |   2.821292   .2055344    13.73   0.000     2.418452    3.224132
            945  |   2.347684   .2241121    10.48   0.000     1.908432    2.786935
            967  |   3.331073   .2110905    15.78   0.000     2.917343    3.744803
            969  |   1.213907   .2445173     4.96   0.000     .7346616    1.693152
            973  |   2.241353   .2480833     9.03   0.000     1.755119    2.727588
            984  |   2.997393   .2035501    14.73   0.000     2.598442    3.396344
            990  |   2.286392   .3032539     7.54   0.000     1.692025    2.880759
            993  |    1.28837    .171445     7.51   0.000     .9523437    1.624396
           1013  |  -1.371321   .0856886   -16.00   0.000    -1.539268   -1.203374
           1015  |    1.02728   .1595316     6.44   0.000     .7146042    1.339957
           1029  |   2.561747   .2228687    11.49   0.000     2.124933    2.998562
           1045  |   2.478204   .1704795    14.54   0.000      2.14407    2.812338
           1062  |    3.09518   .2684028    11.53   0.000     2.569121     3.62124
           1072  |   1.377866   .1367992    10.07   0.000     1.109744    1.645987
           1110  |   2.948464   .2122645    13.89   0.000     2.532433    3.364495
           1118  |  -.1902519   .2859884    -0.67   0.506     -.750779    .3702751
           1120  |   2.882344   .2629272    10.96   0.000     2.367016    3.397672
           1137  |   2.374037   .1992569    11.91   0.000     1.983501    2.764574
           1154  |   3.874382   .1937065    20.00   0.000     3.494725     4.25404
           1192  |   2.621435   .2548017    10.29   0.000     2.122033    3.120837
           1206  |   1.833199     .30448     6.02   0.000     1.236429    2.429969
           1234  |    2.04604    .230311     8.88   0.000     1.594639    2.497441
           1245  |   2.069419   .2064591    10.02   0.000     1.664766    2.474071
           1284  |   3.301093   .3459513     9.54   0.000      2.62304    3.979145
           1292  |   5.109915    .216394    23.61   0.000     4.685791    5.534039
           1338  |   3.045277   .3014652    10.10   0.000     2.454416    3.636138
           1361  |   2.375637   .2099827    11.31   0.000     1.964078    2.787195
           1378  |   1.994741   .2199587     9.07   0.000      1.56363    2.425852
           1384  |    -2.3584   .3044274    -7.75   0.000    -2.955067   -1.761733
           1409  |   1.195849   .1738872     6.88   0.000     .8550368    1.536662
           1418  |   1.346133   .1124728    11.97   0.000     1.125691    1.566576
           1421  |   1.288533   .1906837     6.76   0.000     .9147994    1.662266
           1429  |   1.553403   .2121516     7.32   0.000     1.137593    1.969212
           1432  |   -2.25533   .3472787    -6.49   0.000    -2.935984   -1.574677
           1436  |   1.386625   .1584936     8.75   0.000     1.075983    1.697267
           1448  |   4.083333   .1950897    20.93   0.000     3.700964    4.465701
           1461  |   4.480729    .256477    17.47   0.000     3.978043    4.983415
           1463  |   4.244781   .2920053    14.54   0.000     3.672461    4.817101
           1465  |  -.1924874   .1705691    -1.13   0.259    -.5267967    .1418219
           1493  |   3.285607   .2272736    14.46   0.000     2.840159    3.731056
           1520  |  -3.936182   .5580589    -7.05   0.000    -5.029958   -2.842407
           1521  |    2.49952   .2400355    10.41   0.000     2.029059    2.969981
           1546  |   3.021749   .2845195    10.62   0.000     2.464101    3.579397
           1556  |   1.033432   .2508471     4.12   0.000     .5417804    1.525083
           1573  |    4.79507   .2782488    17.23   0.000     4.249712    5.340428
           1575  |    1.53952   .1809592     8.51   0.000     1.184847    1.894194
           1582  |   3.505622   .1942177    18.05   0.000     3.124962    3.886282
           1591  |   1.015307   .1572436     6.46   0.000      .707115    1.323499
           1592  |   2.927593     .25333    11.56   0.000     2.431076    3.424111
           1594  |   2.751257   .2324311    11.84   0.000       2.2957    3.206814
           1597  |   .3310102    .196162     1.69   0.092    -.0534603    .7154806
           1605  |   1.671898   .1843651     9.07   0.000     1.310549    2.033247
           1620  |   1.046976   .2974948     3.52   0.000     .4638971    1.630055
           1629  |   3.570018   .2240259    15.94   0.000     3.130936    4.009101
           1644  |    4.00258   .2580578    15.51   0.000     3.496796    4.508364
           1666  |   .8548075   .1591609     5.37   0.000     .5428577    1.166757
           1727  |   2.622228   .3000391     8.74   0.000     2.034162    3.210294
           1759  |   1.882108   .1594231    11.81   0.000     1.569644    2.194571
           1970  |   3.860733   .2645667    14.59   0.000     3.342192    4.379274
           2091  |   1.583941   .1373902    11.53   0.000     1.314661    1.853221
           2154  |   7.823191   .2190571    35.71   0.000     7.393847    8.252535
           2155  |   2.523122   .2478997    10.18   0.000     2.037247    3.008996
           2217  |   3.569856   .2065064    17.29   0.000     3.165111    3.974601
           2253  |   1.896435   .2404133     7.89   0.000     1.425234    2.367636
           2255  |   2.440355   .1964686    12.42   0.000     2.055283    2.825426
           2256  |   .5644515   .0774778     7.29   0.000     .4125978    .7163051
           2261  |   1.454029   .2130004     6.83   0.000     1.036556    1.871503
           2263  |    3.53248   .2286869    15.45   0.000     3.084261    3.980698
           2337  |   2.820045   .1814151    15.54   0.000     2.464478    3.175612
           2341  |  -1.061647   .2838237    -3.74   0.000    -1.617931   -.5053624
           2346  |   3.307797   .1345357    24.59   0.000     3.044112    3.571482
           2375  |   .8603371   .1073834     8.01   0.000     .6498695    1.070805
           2380  |   2.223176   .2656093     8.37   0.000     1.702592    2.743761
           2395  |   1.709967    .127543    13.41   0.000     1.459988    1.959947
           2600  |   .0895664   .0719534     1.24   0.213    -.0514597    .2305925
           2623  |  -.1009769   .0892827    -1.13   0.258    -.2759678    .0740141
           2625  |   2.476308   .2271656    10.90   0.000     2.031072    2.921545
           2647  |   .1423069   .2565662     0.55   0.579    -.3605537    .6451674
           2659  |   2.687528   .2138778    12.57   0.000     2.268336    3.106721
           2668  |   2.777728   .1866779    14.88   0.000     2.411846     3.14361
           2670  |   1.749954   .2383456     7.34   0.000     1.282806    2.217103
           2717  |   .1963447   .1449801     1.35   0.176    -.0878111    .4805006
           2724  |   1.856096   .2497069     7.43   0.000     1.366679    2.345513
           2729  |   1.585128   .1821915     8.70   0.000     1.228039    1.942217
           2730  |   .0771593   .2374198     0.32   0.745     -.388175    .5424937
           2740  |   1.809606   .1943261     9.31   0.000     1.428734    2.190479
           2750  |   1.400941   .1600461     8.75   0.000     1.087256    1.714625
           2751  |  -.6416009   .1114389    -5.76   0.000    -.8600171   -.4231847
                 |
           _cons |  -4.341952   .3309132   -13.12   0.000     -4.99053   -3.693374
----------------------------------------------------------------------------------
Note: 0 failures and 46 successes completely determined.

. est store inter

. 
. * Run models for each party family
. levelsof pg_party_family_name if inlist(pg_party_family_name,  "Green_Ecologist","Communist_Socialist", "Social
> _democracy", "Christian_democracy", "Conservative", "Liberal", "Right_wing"), local(groups)
`"Christian_democracy"' `"Communist_Socialist"' `"Conservative"' `"Green_Ecologist"' `"Liberal"' `"Right_wing"' `
> "Social_democracy"'

. local estimates_list // 

. foreach g of local groups {
  2.         di "`g'"
  3.    logit faces_any_fem c.fem_audience  c.audience_avg_age  c.nfaces i.parlgov_id [iweight=1/n_ads] if pg_par
> ty_family_name ==  "`g'", cluster(parlgov_id) 
  4.         est store `g'
  5. 
. }
Christian_democracy

Iteration 0:   log pseudolikelihood = -10.510034  
Iteration 1:   log pseudolikelihood = -7.9050405  
Iteration 2:   log pseudolikelihood = -6.6799746  
Iteration 3:   log pseudolikelihood = -6.3731708  
Iteration 4:   log pseudolikelihood = -6.3681235  
Iteration 5:   log pseudolikelihood = -6.3680835  
Iteration 6:   log pseudolikelihood = -6.3680834  

Logistic regression                                     Number of obs = 10,921
                                                        Wald chi2(2)  =      .
                                                        Prob > chi2   =      .
Log pseudolikelihood = -6.3680834                       Pseudo R2     = 0.3941

                                (Std. err. adjusted for 16 clusters in parlgov_id)
----------------------------------------------------------------------------------
                 |               Robust
   faces_any_fem | Coefficient  std. err.      z    P>|z|     [95% conf. interval]
-----------------+----------------------------------------------------------------
    fem_audience |    .008002   1.470362     0.01   0.996    -2.873855    2.889859
audience_avg_age |  -.0257534    .022212    -1.16   0.246    -.0692881    .0177812
          nfaces |   1.965439   .5273054     3.73   0.000     .9319394    2.998939
                 |
      parlgov_id |
            235  |   2.166513   .4894995     4.43   0.000     1.207111    3.125914
            276  |   1.241007   .1418054     8.75   0.000      .963074    1.518941
            282  |    2.18304   .2538541     8.60   0.000     1.685495    2.680585
            723  |   1.208782   .1764376     6.85   0.000     .8629707    1.554593
           1013  |  -4.038198   .9635199    -4.19   0.000    -5.926662   -2.149733
           1192  |   1.185681   .1824633     6.50   0.000     .8280597    1.543303
           1206  |   .7558454   .4183873     1.81   0.071    -.0641786    1.575869
           1234  |    .411877   .1135366     3.63   0.000     .1893495    .6344046
           1245  |   .5282008   .2540971     2.08   0.038     .0301796    1.026222
           1361  |   .7429794   .0816593     9.10   0.000     .5829301    .9030287
           1432  |  -6.307501   1.888869    -3.34   0.001    -10.00962   -2.605386
           1463  |   3.262493   .5409837     6.03   0.000     2.202184    4.322801
           1727  |   1.406611   .2653145     5.30   0.000     .8866046    1.926618
           2395  |  -.4966362   .4553617    -1.09   0.275    -1.389129    .3958564
           2750  |  -.4076007   .5461308    -0.75   0.455    -1.477997    .6627961
                 |
           _cons |  -2.133982   1.176138    -1.81   0.070    -4.439171    .1712061
----------------------------------------------------------------------------------
Note: 0 failures and 2 successes completely determined.
Communist_Socialist

Iteration 0:   log pseudolikelihood =  -8.923319  
Iteration 1:   log pseudolikelihood = -7.1778874  
Iteration 2:   log pseudolikelihood = -7.1052396  
Iteration 3:   log pseudolikelihood = -7.1040523  
Iteration 4:   log pseudolikelihood = -7.1040519  

Logistic regression                                     Number of obs =  2,186
                                                        Wald chi2(2)  =      .
                                                        Prob > chi2   =      .
Log pseudolikelihood = -7.1040519                       Pseudo R2     = 0.2039

                                (Std. err. adjusted for 13 clusters in parlgov_id)
----------------------------------------------------------------------------------
                 |               Robust
   faces_any_fem | Coefficient  std. err.      z    P>|z|     [95% conf. interval]
-----------------+----------------------------------------------------------------
    fem_audience |   .8340462   1.197383     0.70   0.486    -1.512781    3.180873
audience_avg_age |  -.0283503   .0202317    -1.40   0.161    -.0680037    .0113031
          nfaces |   .9537183   .7898026     1.21   0.227    -.5942664    2.501703
                 |
      parlgov_id |
            256  |  -.2526832   .4473039    -0.56   0.572    -1.129383    .6240163
            306  |   .6337736   .6426624     0.99   0.324    -.6258215    1.893369
            357  |   .7620539   .4882105     1.56   0.119    -.1948211    1.718929
            457  |   .6917538   .5417211     1.28   0.202         -.37    1.753508
            572  |   .0131228   .4727538     0.03   0.978    -.9134576    .9397032
            791  |   .3266613   .6574458     0.50   0.619    -.9619088    1.615231
            882  |  -.3545606   .5105083    -0.69   0.487    -1.355139    .6460174
           1292  |   2.559184   .5514825     4.64   0.000     1.478298     3.64007
           1592  |   .6060639   .5203955     1.16   0.244    -.4138926     1.62602
           2217  |   1.329411   .3209322     4.14   0.000      .700396    1.958427
           2670  |  -.4563843   .4632662    -0.99   0.325    -1.364369    .4516007
           2724  |  -.4732045   .5422575    -0.87   0.383     -1.53601    .5896006
                 |
           _cons |  -.7953532   1.401689    -0.57   0.570    -3.542614    1.951907
----------------------------------------------------------------------------------
Conservative

Iteration 0:   log pseudolikelihood = -17.572647  
Iteration 1:   log pseudolikelihood = -11.454077  
Iteration 2:   log pseudolikelihood = -11.066336  
Iteration 3:   log pseudolikelihood = -11.055668  
Iteration 4:   log pseudolikelihood = -11.055628  
Iteration 5:   log pseudolikelihood = -11.055628  

Logistic regression                                     Number of obs =  9,273
                                                        Wald chi2(2)  =      .
                                                        Prob > chi2   =      .
Log pseudolikelihood = -11.055628                       Pseudo R2     = 0.3709

                                (Std. err. adjusted for 29 clusters in parlgov_id)
----------------------------------------------------------------------------------
                 |               Robust
   faces_any_fem | Coefficient  std. err.      z    P>|z|     [95% conf. interval]
-----------------+----------------------------------------------------------------
    fem_audience |   1.393356   .5565261     2.50   0.012     .3025853    2.484128
audience_avg_age |   .0108693   .0099432     1.09   0.274    -.0086189    .0303576
          nfaces |    1.42577   .2649088     5.38   0.000     .9065587    1.944982
                 |
      parlgov_id |
            280  |   2.664115   .4101689     6.50   0.000     1.860199    3.468031
            363  |    2.02216   .3200981     6.32   0.000     1.394779    2.649541
            417  |   1.492118   .3078718     4.85   0.000     .8886998    2.095535
            437  |   .4710064   .3848739     1.22   0.221    -.2833326    1.225345
            438  |    3.26351   .3468983     9.41   0.000     2.583601    3.943418
            501  |    1.41361   .2705513     5.22   0.000     .8833388     1.94388
            512  |     1.8312   .5165633     3.54   0.000     .8187547    2.843646
            528  |   3.420345     .53527     6.39   0.000     2.371235    4.469455
            590  |   1.285436   .3615126     3.56   0.000     .5768841    1.993987
            596  |   .0503768   .3865632     0.13   0.896     -.707273    .8080267
            645  |   .2961437   .4689548     0.63   0.528    -.6229908    1.215278
            657  |   1.569122   .4024797     3.90   0.000     .7802759    2.357967
            773  |   3.288644   .4496162     7.31   0.000     2.407412    4.169875
            829  |   1.242287   .2840309     4.37   0.000     .6855971    1.798978
            851  |  -.1329798    .292393    -0.45   0.649    -.7060597       .4401
            984  |   2.981621   .3452911     8.64   0.000     2.304863    3.658379
           1045  |   2.349388   .3028586     7.76   0.000     1.755796     2.94298
           1118  |  -.3366361   .4904539    -0.69   0.492    -1.297908    .6246359
           1421  |   1.313205   .3115555     4.21   0.000     .7025675    1.923843
           1575  |   1.616858   .3005241     5.38   0.000     1.027841    2.205874
           1582  |   3.499294   .3487551    10.03   0.000     2.815747    4.182842
           1597  |   .2375442   .3289689     0.72   0.470     -.407223    .8823115
           1620  |   1.026235   .4988257     2.06   0.040     .0485542    2.003915
           1666  |   .7290418   .2728297     2.67   0.008     .1943054    1.263778
           1759  |    1.90557   .2651165     7.19   0.000     1.385951    2.425188
           2154  |   7.809005   .4150679    18.81   0.000     6.995487    8.622523
           2659  |   2.536317   .3727786     6.80   0.000     1.805684    3.266949
           2717  |   .0027936   .2661818     0.01   0.992    -.5189131    .5245003
                 |
           _cons |  -5.323597   .6497377    -8.19   0.000     -6.59706   -4.050135
----------------------------------------------------------------------------------
Green_Ecologist

Iteration 0:   log pseudolikelihood = -9.6949693  
Iteration 1:   log pseudolikelihood =  -6.539629  
Iteration 2:   log pseudolikelihood = -6.2102349  
Iteration 3:   log pseudolikelihood = -6.1933886  
Iteration 4:   log pseudolikelihood = -6.1933478  
Iteration 5:   log pseudolikelihood = -6.1933478  

Logistic regression                                     Number of obs =  7,298
                                                        Wald chi2(2)  =      .
                                                        Prob > chi2   =      .
Log pseudolikelihood = -6.1933478                       Pseudo R2     = 0.3612

                                (Std. err. adjusted for 14 clusters in parlgov_id)
----------------------------------------------------------------------------------
                 |               Robust
   faces_any_fem | Coefficient  std. err.      z    P>|z|     [95% conf. interval]
-----------------+----------------------------------------------------------------
    fem_audience |  -.1331213   .5997076    -0.22   0.824    -1.308527    1.042284
audience_avg_age |  -.0225152     .01302    -1.73   0.084     -.048034    .0030036
          nfaces |   1.978307   .3228705     6.13   0.000     1.345492    2.611121
                 |
      parlgov_id |
            196  |   .1476562   .2395569     0.62   0.538    -.3218667    .6171791
            310  |   .2750205   .0730099     3.77   0.000     .1319238    .4181172
            360  |   -4.47376   .7241103    -6.18   0.000     -5.89299    -3.05453
            403  |  -.2673118   .1749565    -1.53   0.127    -.6102201    .0755966
            467  |  -.7491555   .2069895    -3.62   0.000    -1.154848   -.3434634
            756  |  -.9255442   .1314588    -7.04   0.000    -1.183199   -.6678898
            772  |   -.092171   .0809816    -1.14   0.255     -.250892      .06655
           1062  |   .5981509    .119845     4.99   0.000     .3632591    .8330428
           1154  |   .7674174   .1923629     3.99   0.000     .3903931    1.144442
           1429  |  -1.484078   .1850252    -8.02   0.000    -1.846721   -1.121435
           1573  |   2.164398   .0661402    32.72   0.000     2.034766    2.294031
           1594  |  -.0707597   .1114245    -0.64   0.525    -.2891477    .1476284
           1644  |   1.473707   .1412567    10.43   0.000     1.196849    1.750565
                 |
           _cons |  -.8684387    .590201    -1.47   0.141    -2.025211     .288334
----------------------------------------------------------------------------------
Liberal

Iteration 0:   log pseudolikelihood = -12.484691  
Iteration 1:   log pseudolikelihood = -9.1373745  
Iteration 2:   log pseudolikelihood = -8.5936346  
Iteration 3:   log pseudolikelihood = -8.5455292  
Iteration 4:   log pseudolikelihood = -8.5430387  
Iteration 5:   log pseudolikelihood =  -8.543011  
Iteration 6:   log pseudolikelihood =  -8.543011  

Logistic regression                                     Number of obs = 14,986
                                                        Wald chi2(2)  =      .
                                                        Prob > chi2   =      .
Log pseudolikelihood = -8.543011                        Pseudo R2     = 0.3157

                                (Std. err. adjusted for 21 clusters in parlgov_id)
----------------------------------------------------------------------------------
                 |               Robust
   faces_any_fem | Coefficient  std. err.      z    P>|z|     [95% conf. interval]
-----------------+----------------------------------------------------------------
    fem_audience |   1.301608   .5446515     2.39   0.017     .2341102    2.369105
audience_avg_age |  -.0161258   .0154696    -1.04   0.297    -.0464456     .014194
          nfaces |    1.49228   .2404128     6.21   0.000     1.021079     1.96348
                 |
      parlgov_id |
            345  |   2.288644   .1749875    13.08   0.000     1.945674    2.631613
            376  |   1.464507   .2422915     6.04   0.000     .9896244     1.93939
            543  |   1.911911   .1883138    10.15   0.000     1.542823       2.281
            581  |   1.539541   .0711188    21.65   0.000     1.400151    1.678932
            585  |   2.219163   .0948645    23.39   0.000     2.033232    2.405094
            659  |   .0601402   .1810123     0.33   0.740    -.2946373    .4149177
            892  |   1.640831   .1549233    10.59   0.000     1.337187    1.944475
            915  |    2.21368   .3263799     6.78   0.000     1.573987    2.853373
            967  |   2.841809   .1753878    16.20   0.000     2.498055    3.185562
            969  |   .8330209   .1277042     6.52   0.000     .5827253    1.083317
           1015  |   .5398975   .1675111     3.22   0.001     .2115817    .8682132
           1110  |    2.51771   .1193047    21.10   0.000     2.283877    2.751543
           1384  |   -3.62143   .7671641    -4.72   0.000    -5.125044   -2.117816
           1409  |   .6952988   .1954594     3.56   0.000     .3122053    1.078392
           1605  |   1.206195   .1670314     7.22   0.000     .8788196    1.533571
           2255  |   1.872429   .2727362     6.87   0.000     1.337876    2.406982
           2263  |   3.071238   .1566806    19.60   0.000      2.76415    3.378327
           2375  |    .182682   .2028645     0.90   0.368    -.2149251     .580289
           2647  |  -.2151715   .1378605    -1.56   0.119    -.4853732    .0550302
           2751  |   -1.64607   .5028078    -3.27   0.001    -2.631555   -.6605851
                 |
           _cons |  -3.815477   .6919971    -5.51   0.000    -5.171766   -2.459188
----------------------------------------------------------------------------------
Note: 0 failures and 32 successes completely determined.
Right_wing

Iteration 0:   log pseudolikelihood = -6.3293636  
Iteration 1:   log pseudolikelihood = -4.9017996  
Iteration 2:   log pseudolikelihood = -4.8205191  
Iteration 3:   log pseudolikelihood = -4.8197195  
Iteration 4:   log pseudolikelihood = -4.8197187  
Iteration 5:   log pseudolikelihood = -4.8197187  

Logistic regression                                     Number of obs =  1,036
                                                        Wald chi2(2)  =      .
                                                        Prob > chi2   =      .
Log pseudolikelihood = -4.8197187                       Pseudo R2     = 0.2385

                                (Std. err. adjusted for 12 clusters in parlgov_id)
----------------------------------------------------------------------------------
                 |               Robust
   faces_any_fem | Coefficient  std. err.      z    P>|z|     [95% conf. interval]
-----------------+----------------------------------------------------------------
    fem_audience |   .1819921   1.173555     0.16   0.877    -2.118133    2.482118
audience_avg_age |  -.0006646   .0139556    -0.05   0.962    -.0280171    .0266879
          nfaces |   1.052755   .2682148     3.93   0.000     .5270636    1.578446
                 |
      parlgov_id |
            600  |  -.8966594   .1538778    -5.83   0.000    -1.198254   -.5950644
            993  |   .0906522   .1145614     0.79   0.429     -.133884    .3151883
           1072  |   .1395971   .0568598     2.46   0.014      .028154    .2510402
           1418  |   .2005944   .1638029     1.22   0.221    -.1204534    .5216423
           1436  |   .2000936    .100844     1.98   0.047     .0024431    .3977441
           1546  |   1.634238   .2391755     6.83   0.000     1.165463    2.103014
           2091  |   .2412019   .1867567     1.29   0.197    -.1248345    .6072383
           2253  |   .4455651   .2735137     1.63   0.103     -.090512    .9816421
           2380  |   .7786442    .254321     3.06   0.002     .2801843    1.277104
           2600  |  -1.024212    .175337    -5.84   0.000    -1.367866    -.680558
           2623  |  -1.236574   .0956705   -12.93   0.000    -1.424085   -1.049063
                 |
           _cons |  -2.736291   .6008604    -4.55   0.000    -3.913956   -1.558626
----------------------------------------------------------------------------------
Social_democracy

Iteration 0:   log pseudolikelihood = -21.721699  
Iteration 1:   log pseudolikelihood = -17.461719  
Iteration 2:   log pseudolikelihood = -16.937682  
Iteration 3:   log pseudolikelihood = -16.905185  
Iteration 4:   log pseudolikelihood = -16.904389  
Iteration 5:   log pseudolikelihood = -16.904387  
Iteration 6:   log pseudolikelihood = -16.904387  

Logistic regression                                     Number of obs = 15,036
                                                        Wald chi2(2)  =      .
                                                        Prob > chi2   =      .
Log pseudolikelihood = -16.904387                       Pseudo R2     = 0.2218

                                (Std. err. adjusted for 32 clusters in parlgov_id)
----------------------------------------------------------------------------------
                 |               Robust
   faces_any_fem | Coefficient  std. err.      z    P>|z|     [95% conf. interval]
-----------------+----------------------------------------------------------------
    fem_audience |   1.055545   .3648204     2.89   0.004     .3405103     1.77058
audience_avg_age |   .0011664   .0070626     0.17   0.869     -.012676    .0150088
          nfaces |   .8696901   .2978123     2.92   0.003     .2859887    1.453391
                 |
      parlgov_id |
            318  |   2.268501   .1976273    11.48   0.000     1.881159    2.655844
            382  |   .7502555   .0730725    10.27   0.000      .607036     .893475
            395  |   2.491592    .042788    58.23   0.000     2.407729    2.575455
            558  |   1.239884   .2069305     5.99   0.000     .8343077     1.64546
            701  |   1.076444   .0917097    11.74   0.000     .8966969    1.256192
            706  |   1.661348   .1011009    16.43   0.000     1.463194    1.859503
            742  |   .5399826   .0437833    12.33   0.000      .454169    .6257962
            789  |    1.07556   .0408003    26.36   0.000     .9955932    1.155527
            902  |   1.701828   .2051097     8.30   0.000     1.299821    2.103836
            904  |   1.014115    .100654    10.08   0.000     .8168367    1.211393
            945  |   1.282852   .1109486    11.56   0.000     1.065396    1.500307
            973  |   1.118684   .1582378     7.07   0.000     .8085435    1.428824
           1029  |    1.50504   .0942263    15.97   0.000      1.32036    1.689721
           1120  |   1.734335   .1520203    11.41   0.000      1.43638    2.032289
           1137  |    1.38118   .1246334    11.08   0.000     1.136903    1.625457
           1284  |   1.971087   .3445875     5.72   0.000     1.295708    2.646466
           1338  |   1.806256   .2315489     7.80   0.000     1.352428    2.260083
           1378  |   .9426906   .0907079    10.39   0.000     .7649064    1.120475
           1448  |   3.094582   .0524989    58.95   0.000     2.991686    3.197478
           1493  |   2.227952   .1293036    17.23   0.000     1.974522    2.481383
           1520  |  -3.365574   1.283681    -2.62   0.009    -5.881543   -.8496054
           1556  |  -.0852019   .1397631    -0.61   0.542    -.3591325    .1887286
           1591  |   .1085647   .0555907     1.95   0.051    -.0003911    .2175206
           1629  |   2.518418   .0785918    32.04   0.000     2.364381    2.672455
           1970  |   2.718365    .119755    22.70   0.000      2.48365    2.953081
           2337  |   1.907689   .1035068    18.43   0.000     1.704819    2.110559
           2341  |  -1.131892   .7188322    -1.57   0.115    -2.540778    .2769927
           2346  |   2.458432   .1149652    21.38   0.000     2.233105     2.68376
           2625  |   1.412995   .0986056    14.33   0.000     1.219732    1.606259
           2668  |   1.808751   .0642713    28.14   0.000     1.682782    1.934721
           2740  |   .8291814   .1310021     6.33   0.000     .5724219    1.085941
                 |
           _cons |  -3.226813   .4271002    -7.56   0.000    -4.063914   -2.389712
----------------------------------------------------------------------------------
Note: 0 failures and 8 successes completely determined.

. 
. * Output all models to latex table
. outreg2 [inter Green_Ecologist Communist_Socialist Social_democracy Christian_democracy Conservative Liberal Ri
> ght_wing] using 3.xls, replace drop(i.parlgov_id) label excel tex alpha(0.001, 0.01, 0.05, 0.1) symbol(***, **,
>  *, +)  dec(3) e(N_clust)
3.tex
3.xls
dir : seeout

. 
. 
. *****************************
. * 4 - DV: Only women on image, Controls: Audience age, number of faces
. *****************************
. 
. 
. * Add number of ads per party
. cap drop n_ads

. quietly logit faces_all_fem i.only_women c.audience_avg_age  c.nfaces i.parlgov_id  // Quietly run model to use
>  same observations 

. bysort parlgov_id: gen n_ads=_N if e(sample)
(1,472 missing values generated)

. 
. * Run regression 
. logit faces_all_fem i.only_women c.audience_avg_age  c.nfaces i.parlgov_id [iweight=1/n_ads], cluster(parlgov_i
> d) 

Iteration 0:   log pseudolikelihood = -51.063119  
Iteration 1:   log pseudolikelihood = -41.804364  
Iteration 2:   log pseudolikelihood = -41.414088  
Iteration 3:   log pseudolikelihood = -40.028986  
Iteration 4:   log pseudolikelihood = -40.017754  
Iteration 5:   log pseudolikelihood = -40.017506  
Iteration 6:   log pseudolikelihood = -40.017505  

Logistic regression                                     Number of obs = 61,300
                                                        Wald chi2(7)  =      .
                                                        Prob > chi2   =      .
Log pseudolikelihood = -40.017505                       Pseudo R2     = 0.2163

                               (Std. err. adjusted for 115 clusters in parlgov_id)
----------------------------------------------------------------------------------
                 |               Robust
   faces_all_fem | Coefficient  std. err.      z    P>|z|     [95% conf. interval]
-----------------+----------------------------------------------------------------
    1.only_women |   .8064678   .1969908     4.09   0.000      .420373    1.192563
audience_avg_age |   .0011598   .0049382     0.23   0.814    -.0085189    .0108386
          nfaces |   -.015038   .0409441    -0.37   0.713    -.0952869    .0652109
                 |
      parlgov_id |
            196  |   1.377671   .1080753    12.75   0.000     1.165847    1.589495
            235  |    .894185   .0757419    11.81   0.000     .7457335    1.042636
            256  |   1.345907   .0711698    18.91   0.000     1.206417    1.485397
            276  |    1.04475   .0231881    45.06   0.000     .9993025    1.090198
            280  |   1.170701   .0297169    39.40   0.000     1.112457    1.228945
            282  |   3.561478   .0550095    64.74   0.000     3.453662    3.669295
            306  |    1.11665   .0273758    40.79   0.000     1.062994    1.170306
            310  |   1.529845   .0884653    17.29   0.000     1.356457    1.703234
            311  |   1.270599   .0070516   180.19   0.000     1.256778     1.28442
            318  |   .8646534   .0350841    24.65   0.000     .7958899    .9334169
            345  |   2.123876   .0130547   162.69   0.000      2.09829    2.149463
            357  |   1.895154   .0749406    25.29   0.000     1.748273    2.042035
            376  |    1.62369   .0206373    78.68   0.000     1.583241    1.664138
            382  |   .3696328   .0306373    12.06   0.000     .3095848    .4296808
            395  |   2.658217   .0224586   118.36   0.000     2.614199    2.702235
            403  |   1.574872   .0222471    70.79   0.000     1.531268    1.618475
            437  |   .1149916   .0636243     1.81   0.071    -.0097098    .2396929
            457  |   1.685261   .0420542    40.07   0.000     1.602836    1.767686
            467  |  -.2773011   .0126054   -22.00   0.000    -.3020072   -.2525949
            501  |   1.034348    .010161   101.80   0.000     1.014433    1.054264
            512  |   .4080691   .0550107     7.42   0.000     .3002501    .5158882
            528  |    2.82419   .0275101   102.66   0.000     2.770272    2.878109
            543  |   2.095894   .0948856    22.09   0.000     1.909921    2.281866
            558  |   2.004294   .1262216    15.88   0.000     1.756904    2.251684
            572  |   1.210475   .0256934    47.11   0.000     1.160117    1.260833
            581  |   2.285874    .037596    60.80   0.000     2.212187    2.359561
            585  |   2.898114   .0451201    64.23   0.000      2.80968    2.986548
            590  |   1.299411   .0291243    44.62   0.000     1.242329    1.356494
            645  |   .7581598   .1591387     4.76   0.000     .4462536    1.070066
            657  |   1.529537   .0547728    27.93   0.000     1.422184     1.63689
            659  |  -2.267751   .1243637   -18.23   0.000    -2.511499   -2.024003
            701  |     2.4553   .0148143   165.74   0.000     2.426265    2.484336
            706  |   1.207409   .0189407    63.75   0.000     1.170286    1.244532
            723  |   1.467761   .0094288   155.67   0.000     1.449281    1.486241
            756  |     1.4504   .0269731    53.77   0.000     1.397534    1.503267
            757  |   .8636562   .0289259    29.86   0.000     .8069625      .92035
            772  |   .4089126   .0220246    18.57   0.000     .3657452    .4520801
            773  |    3.14992   .0500124    62.98   0.000     3.051897    3.247942
            789  |    2.02354   .0650825    31.09   0.000     1.895981      2.1511
            791  |  -.4796207   .0291642   -16.45   0.000    -.5367814     -.42246
            829  |   1.223218   .0081834   149.48   0.000     1.207179    1.239257
            865  |   1.128424    .029371    38.42   0.000     1.070858     1.18599
            882  |   2.148856   .0826136    26.01   0.000     1.986937    2.310776
            892  |   1.431089   .0113228   126.39   0.000     1.408897    1.453281
            904  |    2.51091   .1396835    17.98   0.000     2.237136    2.784685
            915  |   1.664547   .0573543    29.02   0.000     1.552135    1.776959
            945  |   2.613713   .0219277   119.20   0.000     2.570736    2.656691
            967  |   2.311405   .0226199   102.18   0.000     2.267071    2.355739
            969  |   1.605091   .0469234    34.21   0.000     1.513123    1.697059
            973  |   2.315836   .0327253    70.77   0.000     2.251695    2.379976
            984  |   1.723362    .011699   147.31   0.000     1.700433    1.746292
            990  |   .2744644   .0447867     6.13   0.000     .1866841    .3622447
            993  |  -.3882654   .0111654   -34.77   0.000    -.4101492   -.3663816
           1013  |  -1.806959   .0591865   -30.53   0.000    -1.922963   -1.690956
           1015  |   .8614794   .0436252    19.75   0.000     .7759756    .9469833
           1029  |    2.20815   .0216819   101.84   0.000     2.165654    2.250646
           1045  |   1.922914   .0267864    71.79   0.000     1.870414    1.975415
           1062  |   1.398765   .0254143    55.04   0.000     1.348954    1.448576
           1072  |   1.310602   .0168439    77.81   0.000     1.277589    1.343616
           1110  |   2.508217   .0289373    86.68   0.000     2.451501    2.564933
           1118  |   .1003717    .065971     1.52   0.128    -.0289291    .2296725
           1120  |   1.607794   .0411409    39.08   0.000     1.527159    1.688429
           1137  |   2.529256   .0214069   118.15   0.000       2.4873    2.571213
           1154  |   3.234411   .0591202    54.71   0.000     3.118538    3.350285
           1192  |   2.325466   .0289284    80.39   0.000     2.268767    2.382164
           1206  |   1.212886   .0352993    34.36   0.000       1.1437    1.282071
           1234  |   1.777529   .0184096    96.55   0.000     1.741447    1.813611
           1245  |   1.704138   .0765371    22.27   0.000     1.554128    1.854148
           1277  |   5.025955   .0582548    86.28   0.000     4.911778    5.140132
           1292  |   5.276332   .0492095   107.22   0.000     5.179883    5.372781
           1338  |   2.751219   .0589442    46.67   0.000      2.63569    2.866747
           1361  |  -.6002203   .0160742   -37.34   0.000    -.6317252   -.5687154
           1378  |   1.663053   .0252713    65.81   0.000     1.613522    1.712584
           1421  |    1.98232   .0189958   104.36   0.000     1.945089    2.019551
           1429  |   .8347592   .0466966    17.88   0.000     .7432355    .9262829
           1448  |   4.164353   .0479525    86.84   0.000     4.070368    4.258339
           1461  |   3.821551   .0325182   117.52   0.000     3.757817    3.885286
           1493  |   1.665098   .0326562    50.99   0.000     1.601093    1.729103
           1521  |   2.865946    .020733   138.23   0.000      2.82531    2.906581
           1546  |   2.034917    .050422    40.36   0.000     1.936091    2.133742
           1556  |  -2.016423   .0272886   -73.89   0.000    -2.069908   -1.962939
           1575  |   1.542335   .0176102    87.58   0.000     1.507819     1.57685
           1591  |  -.0442657   .0226536    -1.95   0.051     -.088666    .0001346
           1594  |    1.75858   .0021754   808.38   0.000     1.754316    1.762844
           1597  |   .1239328    .012281    10.09   0.000     .0998624    .1480032
           1605  |   .4697417    .025048    18.75   0.000     .4206486    .5188349
           1629  |    3.37062   .0176743   190.71   0.000     3.335979    3.405261
           1644  |    2.94713   .0330632    89.14   0.000     2.882328    3.011933
           1666  |   .9572588   .0010065   951.06   0.000     .9552861    .9592316
           1727  |   1.183403   .0328054    36.07   0.000     1.119106    1.247701
           1759  |  -.3575459   .0429064    -8.33   0.000    -.4416409   -.2734509
           1970  |   4.091811   .0745323    54.90   0.000      3.94573    4.237892
           2154  |    5.58793   .0467917   119.42   0.000      5.49622     5.67964
           2155  |   .3003881   .0536197     5.60   0.000     .1952954    .4054808
           2255  |   1.738018     .03572    48.66   0.000     1.668008    1.808028
           2256  |  -.6913824   .0234813   -29.44   0.000    -.7374049   -.6453598
           2261  |   -.151715   .0239184    -6.34   0.000    -.1985942   -.1048358
           2337  |   1.441165   .0651618    22.12   0.000      1.31345     1.56888
           2341  |  -.2920439   .0428591    -6.81   0.000    -.3760461   -.2080416
           2375  |   -.376559   .0695025    -5.42   0.000    -.5127813   -.2403367
           2380  |   2.121791   .0576499    36.80   0.000     2.008799    2.234783
           2623  |   .9825312   .0134695    72.94   0.000     .9561314    1.008931
           2625  |  -.4043313   .0752493    -5.37   0.000    -.5518173   -.2568453
           2647  |   .1333624   .0864441     1.54   0.123    -.0360649    .3027898
           2659  |   3.168412   .0326282    97.11   0.000     3.104462    3.232362
           2668  |   3.017452   .0309678    97.44   0.000     2.956756    3.078148
           2670  |   1.125166   .0437201    25.74   0.000     1.039476    1.210856
           2717  |   -.033259    .043101    -0.77   0.440    -.1177354    .0512174
           2724  |   .6314588   .0402775    15.68   0.000     .5525163    .7104014
           2729  |   1.118783   .0596543    18.75   0.000     1.001863    1.235703
           2730  |    .154699   .0785708     1.97   0.049      .000703     .308695
           2740  |   2.282724   .0335791    67.98   0.000      2.21691    2.348538
           2750  |   1.550107   .0138607   111.84   0.000     1.522941    1.577274
           2751  |  -.6017442   .0115601   -52.05   0.000    -.6244016   -.5790869
                 |
           _cons |   -3.65121   .1801023   -20.27   0.000    -4.004204   -3.298215
----------------------------------------------------------------------------------

. est store inter

. 
. * Run models for each party family
. levelsof pg_party_family_name if inlist(pg_party_family_name,  "Green_Ecologist","Communist_Socialist", "Social
> _democracy", "Christian_democracy", "Conservative", "Liberal", "Right_wing"), local(groups)
`"Christian_democracy"' `"Communist_Socialist"' `"Conservative"' `"Green_Ecologist"' `"Liberal"' `"Right_wing"' `
> "Social_democracy"'

. local estimates_list // 

. foreach g of local groups {
  2.         di "`g'"
  3.    logit  faces_all_fem i.only_women c.audience_avg_age  c.nfaces i.parlgov_id [iweight=1/n_ads] if pg_party
> _family_name ==  "`g'", cluster(parlgov_id) 
  4.         est store `g'
  5. 
. }
Christian_democracy

Iteration 0:   log pseudolikelihood = -4.6159633  
Iteration 1:   log pseudolikelihood = -4.1086091  
Iteration 2:   log pseudolikelihood = -3.8525935  
Iteration 3:   log pseudolikelihood = -3.8214422  
Iteration 4:   log pseudolikelihood = -3.8197238  
Iteration 5:   log pseudolikelihood = -3.8196909  
Iteration 6:   log pseudolikelihood = -3.8196908  

Logistic regression                                     Number of obs = 10,767
                                                        Wald chi2(3)  =      .
                                                        Prob > chi2   =      .
Log pseudolikelihood = -3.8196908                       Pseudo R2     = 0.1725

                                (Std. err. adjusted for 12 clusters in parlgov_id)
----------------------------------------------------------------------------------
                 |               Robust
   faces_all_fem | Coefficient  std. err.      z    P>|z|     [95% conf. interval]
-----------------+----------------------------------------------------------------
    1.only_women |   1.638182    .641564     2.55   0.011     .3807393    2.895624
audience_avg_age |  -.0146559   .0184194    -0.80   0.426    -.0507573    .0214456
          nfaces |   .1232007   .1132107     1.09   0.276    -.0986883    .3450896
                 |
      parlgov_id |
            276  |  -.1976728   .2882876    -0.69   0.493    -.7627062    .3673606
            282  |   2.547302   .0676103    37.68   0.000     2.414788    2.679816
            723  |   .3263469   .2639458     1.24   0.216    -.1909773    .8436711
           1013  |  -3.170474   .2873093   -11.04   0.000     -3.73359   -2.607358
           1192  |    1.08689   .3567291     3.05   0.002      .387714    1.786066
           1206  |   .1734542   .2556403     0.68   0.497    -.3275915       .6745
           1234  |   .5302099   .3523771     1.50   0.132    -.1604367    1.220856
           1245  |   .2052992   .4012796     0.51   0.609    -.5811943    .9917927
           1361  |  -1.719264   .2257912    -7.61   0.000    -2.161807   -1.276722
           1727  |   .0994993   .3009087     0.33   0.741    -.4902709    .6892695
           2750  |   .3173007   .3138661     1.01   0.312    -.2978656    .9324669
                 |
           _cons |  -2.045794   .9508482    -2.15   0.031    -3.909422   -.1821655
----------------------------------------------------------------------------------
Communist_Socialist

Iteration 0:   log pseudolikelihood = -4.6364055  
Iteration 1:   log pseudolikelihood = -3.3451128  
Iteration 2:   log pseudolikelihood = -3.2216022  
Iteration 3:   log pseudolikelihood = -3.2041917  
Iteration 4:   log pseudolikelihood = -3.2036846  
Iteration 5:   log pseudolikelihood = -3.2036841  
Iteration 6:   log pseudolikelihood = -3.2036841  

Logistic regression                                     Number of obs =  2,130
                                                        Wald chi2(2)  =      .
                                                        Prob > chi2   =      .
Log pseudolikelihood = -3.2036841                       Pseudo R2     = 0.3090

                                (Std. err. adjusted for 10 clusters in parlgov_id)
----------------------------------------------------------------------------------
                 |               Robust
   faces_all_fem | Coefficient  std. err.      z    P>|z|     [95% conf. interval]
-----------------+----------------------------------------------------------------
    1.only_women |   .6472886   .1755441     3.69   0.000     .3032284    .9913488
audience_avg_age |   -.008539   .0091755    -0.93   0.352    -.0265226    .0094446
          nfaces |  -.0099251   .0992143    -0.10   0.920    -.2043816    .1845314
                 |
      parlgov_id |
            306  |  -.2256704   .2317991    -0.97   0.330    -.6799883    .2286474
            357  |   .6698493   .2362128     2.84   0.005     .2068807    1.132818
            457  |    .236956   .2229092     1.06   0.288    -.1999379    .6738499
            572  |  -.1214571   .2158388    -0.56   0.574    -.5444934    .3015792
            791  |  -1.832837   .2450459    -7.48   0.000    -2.313118   -1.352556
            882  |   .8542629   .2015275     4.24   0.000     .4592762     1.24925
           1292  |   3.815761   .2197205    17.37   0.000     3.385117    4.246405
           2670  |  -.1629911   .2156407    -0.76   0.450     -.585639    .2596568
           2724  |  -.6933199   .2258862    -3.07   0.002    -1.136049   -.2505911
                 |
           _cons |  -1.929441   .4637202    -4.16   0.000    -2.838316   -1.020566
----------------------------------------------------------------------------------
Conservative

Iteration 0:   log pseudolikelihood = -9.1286327  
Iteration 1:   log pseudolikelihood = -6.9839244  
Iteration 2:   log pseudolikelihood = -6.7658864  
Iteration 3:   log pseudolikelihood = -6.6980413  
Iteration 4:   log pseudolikelihood = -6.6971961  
Iteration 5:   log pseudolikelihood = -6.6971939  
Iteration 6:   log pseudolikelihood = -6.6971939  

Logistic regression                                     Number of obs =  9,002
                                                        Wald chi2(2)  =      .
                                                        Prob > chi2   =      .
Log pseudolikelihood = -6.6971939                       Pseudo R2     = 0.2664

                                (Std. err. adjusted for 21 clusters in parlgov_id)
----------------------------------------------------------------------------------
                 |               Robust
   faces_all_fem | Coefficient  std. err.      z    P>|z|     [95% conf. interval]
-----------------+----------------------------------------------------------------
    1.only_women |  -.2673269   .4715369    -0.57   0.571    -1.191522    .6568685
audience_avg_age |   .0259729   .0120373     2.16   0.031     .0023802    .0495656
          nfaces |   .0059907   .1474923     0.04   0.968    -.2830888    .2950702
                 |
      parlgov_id |
            437  |  -1.446034   .1708897    -8.46   0.000    -1.780972   -1.111096
            501  |  -.2592952   .0568796    -4.56   0.000    -.3707772   -.1478132
            512  |  -1.026855   .1696207    -6.05   0.000    -1.359306   -.6944048
            528  |   1.436472   .0856546    16.77   0.000     1.268592    1.604352
            590  |  -.1017858   .1078181    -0.94   0.345    -.3131055    .1095339
            645  |  -.1632105    .246799    -0.66   0.508    -.6469277    .3205066
            657  |   .0474838    .145317     0.33   0.744    -.2373323    .3322998
            773  |   1.676366   .1343365    12.48   0.000     1.413071     1.93966
            829  |  -.0711213   .0523149    -1.36   0.174    -.1736567     .031414
            984  |   .3971622   .0532016     7.47   0.000     .2928889    .5014355
           1045  |   .5242228   .1083003     4.84   0.000     .3119581    .7364874
           1118  |  -1.455456   .1781952    -8.17   0.000    -1.804712     -1.1062
           1421  |    .789217   .0489759    16.11   0.000      .693226     .885208
           1575  |   .3331587   .0708042     4.71   0.000     .1943851    .4719323
           1597  |  -1.217162   .0611982   -19.89   0.000    -1.337109   -1.097216
           1666  |  -.3271439   .0437829    -7.47   0.000    -.4129568   -.2413309
           1759  |  -1.437287   .0290928   -49.40   0.000    -1.494308   -1.380266
           2154  |    4.09694   .1163335    35.22   0.000      3.86893    4.324949
           2659  |   1.715587   .1008126    17.02   0.000     1.517998    1.913176
           2717  |  -1.387799   .0907413   -15.29   0.000    -1.565648   -1.209949
                 |
           _cons |  -3.335955   .4625505    -7.21   0.000    -4.242538   -2.429373
----------------------------------------------------------------------------------
Green_Ecologist

Iteration 0:   log pseudolikelihood = -4.5517203  
Iteration 1:   log pseudolikelihood = -4.1085075  
Iteration 2:   log pseudolikelihood = -3.9943136  
Iteration 3:   log pseudolikelihood = -3.9919286  
Iteration 4:   log pseudolikelihood = -3.9919169  
Iteration 5:   log pseudolikelihood = -3.9919169  

Logistic regression                                     Number of obs =  7,200
                                                        Wald chi2(2)  =      .
                                                        Prob > chi2   =      .
Log pseudolikelihood = -3.9919169                       Pseudo R2     = 0.1230

                                (Std. err. adjusted for 11 clusters in parlgov_id)
----------------------------------------------------------------------------------
                 |               Robust
   faces_all_fem | Coefficient  std. err.      z    P>|z|     [95% conf. interval]
-----------------+----------------------------------------------------------------
    1.only_women |    .596009   .3486504     1.71   0.087    -.0873332    1.279351
audience_avg_age |   .0059421   .0164757     0.36   0.718    -.0263498    .0382339
          nfaces |  -.1603823   .1365533    -1.17   0.240    -.4280219    .1072573
                 |
      parlgov_id |
            310  |   .0593596   .0678797     0.87   0.382    -.0736821    .1924014
            403  |   .0281908   .1410696     0.20   0.842    -.2483005    .3046822
            467  |  -1.813235   .1539069   -11.78   0.000    -2.114887   -1.511583
            756  |    -.10075   .1738761    -0.58   0.562    -.4415409     .240041
            772  |  -1.144644   .1427048    -8.02   0.000     -1.42434    -.864948
           1062  |  -.0884086   .1764916    -0.50   0.616    -.4343259    .2575086
           1154  |    1.79349   .2661288     6.74   0.000     1.271887    2.315093
           1429  |  -.6909227   .1885696    -3.66   0.000    -1.060512    -.321333
           1594  |   .2271652    .144903     1.57   0.117    -.0568394    .5111698
           1644  |   1.394024   .1636498     8.52   0.000     1.073276    1.714772
                 |
           _cons |  -2.154494   .6323409    -3.41   0.001    -3.393859   -.9151285
----------------------------------------------------------------------------------
Liberal

Iteration 0:   log pseudolikelihood = -6.5265366  
Iteration 1:   log pseudolikelihood =  -5.951045  
Iteration 2:   log pseudolikelihood = -5.8263957  
Iteration 3:   log pseudolikelihood = -5.8173312  
Iteration 4:   log pseudolikelihood = -5.8169559  
Iteration 5:   log pseudolikelihood = -5.8169533  
Iteration 6:   log pseudolikelihood = -5.8169533  

Logistic regression                                     Number of obs = 14,827
                                                        Wald chi2(2)  =      .
                                                        Prob > chi2   =      .
Log pseudolikelihood = -5.8169533                       Pseudo R2     = 0.1087

                                (Std. err. adjusted for 17 clusters in parlgov_id)
----------------------------------------------------------------------------------
                 |               Robust
   faces_all_fem | Coefficient  std. err.      z    P>|z|     [95% conf. interval]
-----------------+----------------------------------------------------------------
    1.only_women |   .5239969   .4359805     1.20   0.229    -.3305092    1.378503
audience_avg_age |   .0068921   .0159407     0.43   0.665    -.0243511    .0381353
          nfaces |  -.0024409   .0764543    -0.03   0.975    -.1522886    .1474067
                 |
      parlgov_id |
            376  |  -.5070297   .0356858   -14.21   0.000    -.5769726   -.4370868
            543  |   .0976358   .2030863     0.48   0.631     -.300406    .4956775
            581  |   .1125375    .134617     0.84   0.403     -.151307    .3763821
            585  |   .7096447   .1662285     4.27   0.000     .3838429    1.035447
            659  |  -4.214246   .2492005   -16.91   0.000     -4.70267   -3.725822
            892  |  -.7152488   .0620972   -11.52   0.000     -.836957   -.5935405
            915  |  -.4012876   .1627636    -2.47   0.014    -.7202985   -.0822768
            967  |   .1723722   .0650418     2.65   0.008     .0448926    .2998518
            969  |  -.5679329   .1477749    -3.84   0.000    -.8575665   -.2782994
           1015  |  -1.322322   .1663543    -7.95   0.000    -1.648371    -.996274
           1110  |    .342539   .1139782     3.01   0.003     .1191459    .5659321
           1605  |  -1.677649   .0968086   -17.33   0.000    -1.867391   -1.487908
           2255  |  -.3484996   .0924754    -3.77   0.000    -.5297481   -.1672512
           2375  |  -2.482847   .1676682   -14.81   0.000     -2.81147   -2.154223
           2647  |  -1.956913    .221259    -8.84   0.000    -2.390573   -1.523253
           2751  |  -2.745008   .0560764   -48.95   0.000    -2.854916   -2.635101
                 |
           _cons |  -1.744528   .5717117    -3.05   0.002    -2.865062   -.6239935
----------------------------------------------------------------------------------
Right_wing

note: 0.only_women != 1 predicts failure perfectly;
      0.only_women omitted and 3 obs not used.

note: 1.only_women omitted because of collinearity.
Iteration 0:   log pseudolikelihood = -1.8779881  
Iteration 1:   log pseudolikelihood = -1.7185959  
Iteration 2:   log pseudolikelihood = -1.6833606  
Iteration 3:   log pseudolikelihood =  -1.682871  
Iteration 4:   log pseudolikelihood =   -1.68287  
Iteration 5:   log pseudolikelihood =   -1.68287  

Logistic regression                                     Number of obs =    541
                                                        Wald chi2(1)  =      .
                                                        Prob > chi2   =      .
Log pseudolikelihood = -1.68287                         Pseudo R2     = 0.1039

                                 (Std. err. adjusted for 6 clusters in parlgov_id)
----------------------------------------------------------------------------------
                 |               Robust
   faces_all_fem | Coefficient  std. err.      z    P>|z|     [95% conf. interval]
-----------------+----------------------------------------------------------------
    1.only_women |          0  (empty)
audience_avg_age |  -.0247266   .0298322    -0.83   0.407    -.0831966    .0337434
          nfaces |   .0479226   .1055545     0.45   0.650    -.1589604    .2548056
                 |
      parlgov_id |
            993  |  -.3584037     .02541   -14.10   0.000    -.4082063   -.3086011
           1072  |   1.342872   .0868862    15.46   0.000     1.172578    1.513166
           1546  |   2.275299   .2364608     9.62   0.000     1.811845    2.738754
           2380  |   2.532773   .1750092    14.47   0.000     2.189761    2.875784
           2623  |   .9628218   .0599406    16.06   0.000     .8453405    1.080303
                 |
           _cons |  -2.759484   1.117615    -2.47   0.014    -4.949969   -.5689994
----------------------------------------------------------------------------------
Social_democracy

Iteration 0:   log pseudolikelihood = -14.785599  
Iteration 1:   log pseudolikelihood = -11.952318  
Iteration 2:   log pseudolikelihood = -11.665756  
Iteration 3:   log pseudolikelihood = -11.631682  
Iteration 4:   log pseudolikelihood = -11.629391  
Iteration 5:   log pseudolikelihood = -11.629316  
Iteration 6:   log pseudolikelihood = -11.629316  

Logistic regression                                     Number of obs = 14,918
                                                        Wald chi2(3)  =      .
                                                        Prob > chi2   =      .
Log pseudolikelihood = -11.629316                       Pseudo R2     = 0.2135

                                (Std. err. adjusted for 27 clusters in parlgov_id)
----------------------------------------------------------------------------------
                 |               Robust
   faces_all_fem | Coefficient  std. err.      z    P>|z|     [95% conf. interval]
-----------------+----------------------------------------------------------------
    1.only_women |   .8732585   .3006626     2.90   0.004     .2839707    1.462546
audience_avg_age |   .0010892   .0068681     0.16   0.874    -.0123721    .0145505
          nfaces |  -.0993547   .0819018    -1.21   0.225    -.2598794    .0611699
                 |
      parlgov_id |
            382  |  -.5013636   .0819444    -6.12   0.000    -.6619717   -.3407555
            395  |   1.793295   .0669471    26.79   0.000     1.662081    1.924508
            558  |   1.036319   .2091217     4.96   0.000     .6264479     1.44619
            701  |   1.549608   .0651961    23.77   0.000     1.421826     1.67739
            706  |     .33398   .0677211     4.93   0.000     .2012492    .4667109
            789  |   1.194498   .1086874    10.99   0.000     .9814742    1.407521
            904  |   1.607031   .2247993     7.15   0.000     1.166433     2.04763
            945  |      1.703   .0762842    22.32   0.000     1.553485    1.852514
            973  |   1.384564   .0927582    14.93   0.000     1.202761    1.566366
           1029  |   1.309519   .0750138    17.46   0.000     1.162495    1.456543
           1120  |   .6913775   .1072046     6.45   0.000     .4812602    .9014947
           1137  |   1.638895   .0161442   101.52   0.000     1.607253    1.670537
           1277  |   4.133991    .123649    33.43   0.000     3.891644    4.376339
           1338  |   1.803541   .1352721    13.33   0.000     1.538412     2.06867
           1378  |   .7570496   .0822183     9.21   0.000     .5959047    .9181945
           1448  |    3.30078   .0884118    37.33   0.000     3.127495    3.474064
           1493  |   .8147387   .0266196    30.61   0.000     .7625652    .8669121
           1556  |  -2.937437   .1012202   -29.02   0.000    -3.135825   -2.739049
           1591  |  -.9258537   .0730302   -12.68   0.000     -1.06899   -.7827172
           1629  |   2.491305   .0643975    38.69   0.000     2.365088    2.617522
           1970  |   3.199212   .1461539    21.89   0.000     2.912756    3.485668
           2337  |   .6512256   .1095636     5.94   0.000     .4364849    .8659662
           2341  |  -1.143401   .0936524   -12.21   0.000    -1.326957   -.9598462
           2625  |  -1.261497   .1258411   -10.02   0.000    -1.508141   -1.014853
           2668  |   2.189496   .0628381    34.84   0.000     2.066336    2.312657
           2740  |   1.378756   .0390971    35.26   0.000     1.302127    1.455385
                 |
           _cons |  -2.674194   .2026932   -13.19   0.000    -3.071466   -2.276923
----------------------------------------------------------------------------------

. 
. * Output all models to latex table
. outreg2 [inter Green_Ecologist Communist_Socialist Social_democracy Christian_democracy Conservative Liberal Ri
> ght_wing] using 4.xls, replace drop(i.parlgov_id) label excel tex alpha(0.001, 0.01, 0.05, 0.1) symbol(***, **,
>  *, +)  dec(3) e(N_clust)
4.tex
4.xls
dir : seeout

. 
. 
. *****************************
. * 5 - DV: Any woman on image, Controls: No controls
. *****************************
. 
. 
. * Add number of ads per party
. cap drop n_ads

. quietly logit faces_any_fem i.only_women i.parlgov_id

. bysort parlgov_id: gen n_ads=_N if e(sample)
(89 missing values generated)

. 
. * Run regression 
. logit faces_any_fem i.only_women i.parlgov_id [iweight=1/n_ads] , cluster(parlgov_id)

Iteration 0:   log pseudolikelihood = -97.729537  
Iteration 1:   log pseudolikelihood = -82.662833  
Iteration 2:   log pseudolikelihood =  -82.17659  
Iteration 3:   log pseudolikelihood = -82.153825  
Iteration 4:   log pseudolikelihood = -82.153163  
Iteration 5:   log pseudolikelihood = -82.153161  

Logistic regression                                     Number of obs = 62,683
                                                        Wald chi2(74) =      .
                                                        Prob > chi2   =      .
Log pseudolikelihood = -82.153161                       Pseudo R2     = 0.1594

                            (Std. err. adjusted for 151 clusters in parlgov_id)
-------------------------------------------------------------------------------
              |               Robust
faces_any_fem | Coefficient  std. err.      z    P>|z|     [95% conf. interval]
--------------+----------------------------------------------------------------
 1.only_women |   .6675118   .1768514     3.77   0.000     .3208895    1.014134
              |
   parlgov_id |
          47  |   .1019151    .002553    39.92   0.000     .0969113    .1069189
          50  |   .4534743   9.82e-09  4.6e+07   0.000     .4534743    .4534743
         113  |  -.6614938   .0482064   -13.72   0.000    -.7559767   -.5670109
         118  |   1.540445   9.86e-09  1.6e+08   0.000     1.540445    1.540445
         161  |   .9422894   .0184155    51.17   0.000     .9061957    .9783832
         196  |   2.236566   .0606194    36.90   0.000     2.117754    2.355378
         200  |   .3448405   9.92e-09  3.5e+07   0.000     .3448405    .3448405
         220  |    .054323   .0160245     3.39   0.001     .0229156    .0857303
         235  |   1.791759   9.81e-09  1.8e+08   0.000     1.791759    1.791759
         256  |   1.974081   1.14e-08  1.7e+08   0.000     1.974081    1.974081
         276  |   1.756668   9.82e-09  1.8e+08   0.000     1.756668    1.756668
         280  |   1.312263   .0159296    82.38   0.000     1.281042    1.343485
         282  |   2.482552   .0037429   663.28   0.000     2.475217    2.489888
         306  |   1.485029   9.84e-09  1.5e+08   0.000     1.485029    1.485029
         310  |   1.420741   .0553904    25.65   0.000     1.312178    1.529304
         311  |   .5108256   9.81e-09  5.2e+07   0.000     .5108256    .5108256
         318  |   2.148434   2.23e-08  9.6e+07   0.000     2.148434    2.148434
         345  |   1.466337   9.84e-09  1.5e+08   0.000     1.466337    1.466337
         357  |    1.44817   9.83e-09  1.5e+08   0.000      1.44817     1.44817
         360  |   .0571584   1.32e-08  4.3e+06   0.000     .0571584    .0571584
         363  |   .8183103   9.82e-09  8.3e+07   0.000     .8183103    .8183103
         376  |   .1911516   1.11e-08  1.7e+07   0.000     .1911516    .1911517
         382  |   .9972598   9.81e-09  1.0e+08   0.000     .9972598    .9972598
         395  |   2.696326   .0011398  2365.54   0.000     2.694092     2.69856
         403  |   1.576117   .0054934   286.91   0.000      1.56535    1.586883
         417  |   .4054651   9.83e-09  4.1e+07   0.000     .4054651    .4054651
         437  |  -.4577158   1.11e-08 -4.1e+07   0.000    -.4577158   -.4577158
         438  |   2.527492   .0058874   429.31   0.000     2.515953    2.539031
         457  |   2.171249   2.48e-08  8.8e+07   0.000     2.171249    2.171249
         467  |   1.369765   9.82e-09  1.4e+08   0.000     1.369765    1.369765
         501  |   .5463034   .0015009   363.99   0.000     .5433617     .549245
         512  |   .0246925   .0022868    10.80   0.000     .0202105    .0291746
         520  |   .8754687   9.82e-09  8.9e+07   0.000     .8754687    .8754687
         528  |   1.903341   .0015019  1267.31   0.000     1.900397    1.906285
         543  |   .4637334   .0773641     5.99   0.000     .3121026    .6153643
         558  |    .666042   .1031783     6.46   0.000     .4638163    .8682676
         572  |   .8560506   9.82e-09  8.7e+07   0.000     .8560506    .8560507
         581  |   .8979416   9.82e-09  9.1e+07   0.000     .8979416    .8979416
         585  |   1.398717   9.82e-09  1.4e+08   0.000     1.398717    1.398717
         590  |   .2784986   .0028418    98.00   0.000     .2729287    .2840684
         596  |  -1.386294   1.80e-08 -7.7e+07   0.000    -1.386294   -1.386294
         600  |  -.0091653   .0029266    -3.13   0.002    -.0149012   -.0034293
         645  |  -.7946211   .1166186    -6.81   0.000    -1.023189   -.5660527
         657  |   .2937399   .0072745    40.38   0.000     .2794821    .3079976
         659  |    -.95797   .0988324    -9.69   0.000    -1.151678   -.7642621
         701  |   .9734491   9.81e-09  9.9e+07   0.000     .9734491    .9734492
         706  |   1.627456   9.87e-09  1.6e+08   0.000     1.627456    1.627456
         723  |   1.629555   9.87e-09  1.7e+08   0.000     1.629555    1.629555
         742  |   .8132769   .0031399   259.01   0.000     .8071228    .8194309
         756  |   .7731899   9.82e-09  7.9e+07   0.000     .7731899    .7731899
         757  |    1.54601   .0019221   804.33   0.000     1.542242    1.549777
         772  |   1.374434   .0048984   280.59   0.000     1.364834    1.384035
         773  |   1.977075   .0031699   623.71   0.000     1.970862    1.983288
         789  |   1.452074   .0274981    52.81   0.000     1.398179    1.505969
         791  |   .9938436   .0006776  1466.70   0.000     .9925155    .9951717
         829  |   .3364722   9.94e-09  3.4e+07   0.000     .3364722    .3364722
         851  |  -.3123747   9.88e-09 -3.2e+07   0.000    -.3123747   -.3123747
         865  |   .0870114   1.27e-08  6.8e+06   0.000     .0870114    .0870114
         882  |   .8052305     .06646    12.12   0.000     .6749713    .9354896
         892  |   .9873866   9.81e-09  1.0e+08   0.000     .9873866    .9873867
         902  |   1.339774   9.82e-09  1.4e+08   0.000     1.339774    1.339774
         904  |   .9936105   .1168454     8.50   0.000     .7645978    1.222623
         915  |   1.609438   9.87e-09  1.6e+08   0.000     1.609438    1.609438
         945  |   1.056648   9.81e-09  1.1e+08   0.000     1.056648    1.056648
         967  |   2.445686   7.22e-08  3.4e+07   0.000     2.445686    2.445686
         969  |  -.2109483   1.14e-08 -1.8e+07   0.000    -.2109483   -.2109483
         973  |   .7005114   .0106408    65.83   0.000     .6796558    .7213671
         984  |   1.966113   1.12e-08  1.8e+08   0.000     1.966113    1.966113
         990  |   .6466272   9.81e-09  6.6e+07   0.000     .6466271    .6466272
         993  |   .3474149   .0014761   235.37   0.000     .3445219     .350308
        1013  |  -1.625572   .0355876   -45.68   0.000    -1.695323   -1.555822
        1015  |   .4700088   .0028902   162.62   0.000     .4643442    .4756734
        1029  |   1.455974   9.84e-09  1.5e+08   0.000     1.455974    1.455974
        1045  |   2.049589   1.45e-08  1.4e+08   0.000     2.049589    2.049589
        1062  |   2.251292   3.54e-08  6.4e+07   0.000     2.251292    2.251292
        1072  |   .7375989   9.82e-09  7.5e+07   0.000     .7375989     .737599
        1110  |   1.933571   .0012017  1609.03   0.000     1.931215    1.935926
        1118  |  -1.597495   .0010952 -1458.69   0.000    -1.599641   -1.595348
        1120  |    1.44566   .0012505  1156.07   0.000     1.443209    1.448111
        1137  |   1.455287   9.84e-09  1.5e+08   0.000     1.455287    1.455287
        1154  |   3.068053   1.43e-07  2.1e+07   0.000     3.068053    3.068053
        1192  |   1.179966   .0142123    83.02   0.000      1.15211    1.207821
        1206  |   .1823216   1.12e-08  1.6e+07   0.000     .1823215    .1823216
        1234  |    .935229    .002612   358.05   0.000     .9301095    .9403485
        1245  |   1.086682   .0514773    21.11   0.000     .9857882    1.187575
        1284  |   1.098612   9.81e-09  1.1e+08   0.000     1.098612    1.098612
        1292  |   4.219508   1.05e-08  4.0e+08   0.000     4.219508    4.219508
        1338  |   1.129832   .0153098    73.80   0.000     1.099825    1.159839
        1361  |   1.288656   9.81e-09  1.3e+08   0.000     1.288656    1.288656
        1378  |   .8003919   .0030419   263.12   0.000     .7944298     .806354
        1384  |  -1.041453   4.93e-07 -2.1e+06   0.000    -1.041454   -1.041452
        1409  |   .0119762   1.38e-08  8.7e+05   0.000     .0119762    .0119762
        1418  |   .9044563   9.82e-09  9.2e+07   0.000     .9044562    .9044563
        1421  |   .4795731   9.81e-09  4.9e+07   0.000     .4795731    .4795731
        1429  |   .3935963   .0119186    33.02   0.000     .3702362    .4169564
        1432  |  -.1541507   1.28e-08 -1.2e+07   0.000    -.1541507   -.1541507
        1436  |   .8637727   9.82e-09  8.8e+07   0.000     .8637727    .8637727
        1448  |   3.100785   .0363128    85.39   0.000     3.029613    3.171957
        1461  |   3.058186   .0179701   170.18   0.000     3.022965    3.093406
        1463  |   3.401197   6.75e-08  5.0e+07   0.000     3.401197    3.401197
        1465  |   1.098612   9.81e-09  1.1e+08   0.000     1.098612    1.098612
        1493  |   2.287631   .0034287   667.20   0.000      2.28091    2.294351
        1520  |  -.5108256   1.81e-08 -2.8e+07   0.000    -.5108257   -.5108256
        1521  |   1.482028   .0135045   109.74   0.000      1.45556    1.508496
        1546  |   1.360977   9.82e-09  1.4e+08   0.000     1.360977    1.360977
        1556  |   .0163028   .0014311    11.39   0.000     .0134979    .0191076
        1573  |   3.295837   9.67e-08  3.4e+07   0.000     3.295837    3.295837
        1575  |   .3703738   9.87e-09  3.8e+07   0.000     .3703738    .3703738
        1582  |   2.553899   9.65e-08  2.6e+07   0.000     2.553899      2.5539
        1591  |   .3659343   9.88e-09  3.7e+07   0.000     .3659342    .3659343
        1592  |   1.424035   9.83e-09  1.4e+08   0.000     1.424035    1.424035
        1594  |   1.672571   9.86e-09  1.7e+08   0.000     1.672571    1.672571
        1597  |  -.5436154   2.69e-08 -2.0e+07   0.000    -.5436155   -.5436154
        1605  |   .6448154   .0058648   109.95   0.000     .6333205    .6563103
        1620  |  -.7731897   2.01e-07 -3.8e+06   0.000    -.7731901   -.7731893
        1629  |   2.575058   1.01e-07  2.5e+07   0.000     2.575057    2.575058
        1644  |   2.900189   .0046833   619.27   0.000      2.89101    2.909368
        1666  |   .2876821   1.01e-08  2.8e+07   0.000      .287682    .2876821
        1727  |   .8157089   .0000231  3.5e+04   0.000     .8156637     .815754
        1759  |   .9940337   .0206406    48.16   0.000     .9535788    1.034489
        1970  |   2.703307   .0026969  1002.38   0.000     2.698022    2.708593
        2091  |    .752336   9.82e-09  7.7e+07   0.000      .752336    .7523361
        2154  |   6.527837   .0001217  5.4e+04   0.000     6.527598    6.528075
        2155  |   .9508819   .0244868    38.83   0.000     .9028886    .9988752
        2217  |   2.452298   .0073515   333.58   0.000     2.437889    2.466706
        2253  |   .2231435   1.07e-08  2.1e+07   0.000     .2231435    .2231436
        2255  |   1.190383   .0015948   746.42   0.000     1.187258    1.193509
        2256  |   .1535038   .0142027    10.81   0.000     .1256671    .1813405
        2261  |  -.0198026   1.40e-08 -1.4e+06   0.000    -.0198027   -.0198026
        2263  |   2.351375   5.26e-08  4.5e+07   0.000     2.351375    2.351375
        2337  |   2.419071   .0150443   160.80   0.000     2.389585    2.448558
        2341  |   .2592486   .0050059    51.79   0.000     .2494372    .2690599
        2346  |    2.60269   1.07e-07  2.4e+07   0.000     2.602689     2.60269
        2375  |   .8212924   .0338527    24.26   0.000     .7549423    .8876425
        2380  |   .3268243   .0238697    13.69   0.000     .2800406    .3736081
        2395  |   1.386294   9.82e-09  1.4e+08   0.000     1.386294    1.386294
        2600  |     .24214   1.05e-08  2.3e+07   0.000       .24214    .2421401
        2623  |  -.8472976   2.95e-07 -2.9e+06   0.000    -.8472982    -.847297
        2625  |   1.691778   .0253513    66.73   0.000      1.64209    1.741465
        2647  |  -1.635679   .0515573   -31.73   0.000    -1.736729   -1.534629
        2659  |   1.906599   1.02e-08  1.9e+08   0.000     1.906599    1.906599
        2668  |   1.954278   1.09e-08  1.8e+08   0.000     1.954278    1.954278
        2670  |   .3566749   9.89e-09  3.6e+07   0.000     .3566749     .356675
        2717  |  -.6828458    .015582   -43.82   0.000    -.7133859   -.6523056
        2724  |   .5133707   .0214923    23.89   0.000     .4712466    .5554948
        2729  |   .8593826   9.82e-09  8.8e+07   0.000     .8593826    .8593826
        2730  |   -1.53479   4.66e-07 -3.3e+06   0.000     -1.53479   -1.534789
        2740  |   .8244034   .0180164    45.76   0.000      .789092    .8597149
        2750  |   1.098612   9.81e-09  1.1e+08   0.000     1.098612    1.098612
        2751  |   .0041754   1.38e-08  3.0e+05   0.000     .0041753    .0041754
              |
        _cons |  -1.791759   9.81e-09 -1.8e+08   0.000    -1.791759   -1.791759
-------------------------------------------------------------------------------

. est store inter

. 
. 
. * Run models for each party family
. levelsof pg_party_family_name if inlist(pg_party_family_name,  "Green_Ecologist","Communist_Socialist", "Social
> _democracy", "Christian_democracy", "Conservative", "Liberal", "Right_wing"), local(groups)
`"Christian_democracy"' `"Communist_Socialist"' `"Conservative"' `"Green_Ecologist"' `"Liberal"' `"Right_wing"' `
> "Social_democracy"'

. local estimates_list // 

. foreach g of local groups {
  2.         di "`g'"
  3.     logit faces_any_fem i.only_women  i.parlgov_id [iweight=1/n_ads] if pg_party_family_name ==  "`g'", clus
> ter(parlgov_id)
  4.         est store `g'
  5.         
. }
Christian_democracy

Iteration 0:   log pseudolikelihood = -10.510034  
Iteration 1:   log pseudolikelihood = -9.0731348  
Iteration 2:   log pseudolikelihood = -9.0256423  
Iteration 3:   log pseudolikelihood = -9.0233117  
Iteration 4:   log pseudolikelihood = -9.0233093  
Iteration 5:   log pseudolikelihood = -9.0233093  

Logistic regression                                     Number of obs = 10,921
                                                        Wald chi2(0)  =      .
                                                        Prob > chi2   =      .
Log pseudolikelihood = -9.0233093                       Pseudo R2     = 0.1415

                             (Std. err. adjusted for 16 clusters in parlgov_id)
-------------------------------------------------------------------------------
              |               Robust
faces_any_fem | Coefficient  std. err.      z    P>|z|     [95% conf. interval]
--------------+----------------------------------------------------------------
 1.only_women |   .9768723   .5292537     1.85   0.065    -.0604458     2.01419
              |
   parlgov_id |
         235  |   1.694619   .0086649   195.57   0.000     1.677636    1.711602
         276  |   1.659527   .0086649   191.52   0.000     1.642544     1.67651
         282  |    2.37944   .0005832  4080.32   0.000     2.378297    2.380583
         723  |   1.532414   .0086649   176.85   0.000     1.515431    1.549397
        1013  |  -1.792143   .1229302   -14.58   0.000    -2.033081   -1.551204
        1192  |   1.058122   .0330693    32.00   0.000     .9933073    1.122936
        1206  |   .0851807   .0086649     9.83   0.000     .0681977    .1021637
        1234  |   .8334848   .0007906  1054.25   0.000     .8319352    .8350343
        1245  |   .8985945   .1481102     6.07   0.000     .6083038    1.188885
        1361  |   1.191515   .0086649   137.51   0.000     1.174532    1.208498
        1432  |  -.2512915   .0086649   -29.00   0.000    -.2682745   -.2343085
        1463  |   3.304057   .0086649   381.31   0.000     3.287074     3.32104
        1727  |   .7185271   .0085943    83.61   0.000     .7016825    .7353716
        2395  |   1.289154   .0086649   148.78   0.000     1.272171    1.306136
        2750  |   1.001471   .0086649   115.58   0.000     .9844885    1.018454
              |
        _cons |  -1.694619   .0086649  -195.57   0.000    -1.711602   -1.677636
-------------------------------------------------------------------------------
Communist_Socialist

Iteration 0:   log pseudolikelihood =  -8.923319  
Iteration 1:   log pseudolikelihood = -7.8875889  
Iteration 2:   log pseudolikelihood = -7.8746711  
Iteration 3:   log pseudolikelihood = -7.8745817  
Iteration 4:   log pseudolikelihood = -7.8745817  

Logistic regression                                     Number of obs =  2,186
                                                        Wald chi2(2)  =      .
                                                        Prob > chi2   =      .
Log pseudolikelihood = -7.8745817                       Pseudo R2     = 0.1175

                             (Std. err. adjusted for 13 clusters in parlgov_id)
-------------------------------------------------------------------------------
              |               Robust
faces_any_fem | Coefficient  std. err.      z    P>|z|     [95% conf. interval]
--------------+----------------------------------------------------------------
 1.only_women |   .1534059   .7562094     0.20   0.839    -1.328737    1.635549
              |
   parlgov_id |
         256  |    .433636   2.57e-13  1.7e+12   0.000      .433636     .433636
         306  |  -.0554158   1.08e-15 -5.2e+13   0.000    -.0554158   -.0554158
         357  |  -.0922753   4.46e-15 -2.1e+13   0.000    -.0922753   -.0922753
         457  |    .630804   1.09e-11  5.8e+10   0.000      .630804     .630804
         572  |  -.6843944   2.08e-12 -3.3e+11   0.000    -.6843944   -.6843944
         791  |   -.544705   .0026279  -207.28   0.000    -.5498556   -.5395543
         882  |  -.5509237   .2571903    -2.14   0.032    -1.055007   -.0468401
        1292  |   2.679063   6.78e-08  4.0e+07   0.000     2.679062    2.679063
        1592  |  -.1164104   1.14e-14 -1.0e+13   0.000    -.1164104   -.1164104
        2217  |   .9361537   .0398547    23.49   0.000     .8580398    1.014268
        2670  |   -1.18377   5.64e-11 -2.1e+10   0.000     -1.18377    -1.18377
        2724  |  -.9697587   .0760909   -12.74   0.000    -1.118894   -.8206233
              |
        _cons |  -.2513144   4.59e-16 -5.5e+14   0.000    -.2513144   -.2513144
-------------------------------------------------------------------------------
Conservative

Iteration 0:   log pseudolikelihood = -17.582087  
Iteration 1:   log pseudolikelihood = -13.744758  
Iteration 2:   log pseudolikelihood =  -13.54452  
Iteration 3:   log pseudolikelihood = -13.533581  
Iteration 4:   log pseudolikelihood = -13.533347  
Iteration 5:   log pseudolikelihood = -13.533346  

Logistic regression                                     Number of obs =  9,274
                                                        Wald chi2(13) =      .
                                                        Prob > chi2   =      .
Log pseudolikelihood = -13.533346                       Pseudo R2     = 0.2303

                             (Std. err. adjusted for 29 clusters in parlgov_id)
-------------------------------------------------------------------------------
              |               Robust
faces_any_fem | Coefficient  std. err.      z    P>|z|     [95% conf. interval]
--------------+----------------------------------------------------------------
 1.only_women |   .6831734   .3597873     1.90   0.058    -.0219967    1.388344
              |
   parlgov_id |
         280  |   1.310853   .0323761    40.49   0.000     1.247397    1.374309
         363  |   .8183103   6.76e-09  1.2e+08   0.000     .8183103    .8183103
         417  |   .4054651   6.76e-09  6.0e+07   0.000     .4054651    .4054651
         437  |  -.4577158   6.76e-09 -6.8e+07   0.000    -.4577158   -.4577158
         438  |   2.526973   .0118689   212.91   0.000      2.50371    2.550235
         501  |   .5461702   .0030667   178.10   0.000     .5401596    .5521807
         512  |   .0244892   .0046884     5.22   0.000     .0153002    .0336783
         528  |   1.903208   .0030378   626.50   0.000     1.897254    1.909162
         590  |   .2782461   .0058172    47.83   0.000     .2668446    .2896476
         596  |  -1.386294   2.21e-07 -6.3e+06   0.000    -1.386295   -1.386294
         645  |  -.8049712   .2382862    -3.38   0.001    -1.272004   -.3379388
         657  |   .2930937   .0148884    19.69   0.000     .2639129    .3222745
         773  |   1.976795   .0064093   308.43   0.000     1.964233    1.989357
         829  |   .3364722   6.76e-09  5.0e+07   0.000     .3364722    .3364722
         851  |  -.3123747   9.29e-09 -3.4e+07   0.000    -.3123747   -.3123747
         984  |   1.966113   2.41e-08  8.2e+07   0.000     1.966113    1.966113
        1045  |   2.049589   4.70e-08  4.4e+07   0.000     2.049588    2.049589
        1118  |  -1.597594   .0022585  -707.36   0.000     -1.60202   -1.593167
        1421  |   .4795731   6.76e-09  7.1e+07   0.000     .4795731    .4795731
        1575  |   .3703738   6.76e-09  5.5e+07   0.000     .3703738    .3703738
        1582  |   2.553899   4.62e-07  5.5e+06   0.000     2.553898      2.5539
        1597  |  -.5436155   7.15e-09 -7.6e+07   0.000    -.5436155   -.5436154
        1620  |  -.7731898   9.19e-08 -8.4e+06   0.000      -.77319   -.7731896
        1666  |   .2876821   6.78e-09  4.2e+07   0.000     .2876821    .2876821
        1759  |   .9922046   .0420488    23.60   0.000     .9097905    1.074619
        2154  |   6.527948   .0000101  6.5e+05   0.000     6.527928    6.527968
        2659  |   1.906599   1.38e-08  1.4e+08   0.000     1.906599    1.906599
        2717  |  -.6842329   .0320311   -21.36   0.000    -.7470127   -.6214532
              |
        _cons |  -1.791759   6.76e-09 -2.7e+08   0.000    -1.791759   -1.791759
-------------------------------------------------------------------------------
Green_Ecologist

Iteration 0:   log pseudolikelihood = -9.6949693  
Iteration 1:   log pseudolikelihood = -8.4048201  
Iteration 2:   log pseudolikelihood = -8.4009349  
Iteration 3:   log pseudolikelihood = -8.4009296  
Iteration 4:   log pseudolikelihood = -8.4009296  

Logistic regression                                     Number of obs =  7,298
                                                        Wald chi2(0)  =      .
                                                        Prob > chi2   =      .
Log pseudolikelihood = -8.4009296                       Pseudo R2     = 0.1335

                             (Std. err. adjusted for 14 clusters in parlgov_id)
-------------------------------------------------------------------------------
              |               Robust
faces_any_fem | Coefficient  std. err.      z    P>|z|     [95% conf. interval]
--------------+----------------------------------------------------------------
 1.only_women |    .152669   .1805773     0.85   0.398    -.2012559    .5065939
              |
   parlgov_id |
         196  |   1.431155   .0530255    26.99   0.000     1.327227    1.535083
         310  |   .5886995   .0395072    14.90   0.000     .5112668    .6661321
         360  |   -.936468   .0169655   -55.20   0.000    -.9697198   -.9032161
         403  |   .5990256   .0110875    54.03   0.000     .5772945    .6207567
         467  |   .3761387   .0169655    22.17   0.000     .3428869    .4093905
         756  |  -.2204365   .0169655   -12.99   0.000    -.2536883   -.1871847
         772  |   .3951926   .0119781    32.99   0.000     .3717159    .4186692
        1062  |   1.257665   .0169655    74.13   0.000     1.224414    1.290917
        1154  |   2.074427   .0169655   122.27   0.000     2.041175    2.107678
        1429  |  -.5686792   .0072167   -78.80   0.000    -.5828237   -.5545347
        1573  |    2.30221   .0169655   135.70   0.000     2.268959    2.335462
        1594  |   .6789446   .0169655    40.02   0.000     .6456928    .7121964
        1644  |   1.922711   .0103956   184.95   0.000     1.902336    1.943086
              |
        _cons |  -.7981331   .0169655   -47.04   0.000    -.8313849   -.7648813
-------------------------------------------------------------------------------
Liberal

Iteration 0:   log pseudolikelihood = -12.484691  
Iteration 1:   log pseudolikelihood = -10.833911  
Iteration 2:   log pseudolikelihood = -10.730204  
Iteration 3:   log pseudolikelihood = -10.726999  
Iteration 4:   log pseudolikelihood = -10.726986  
Iteration 5:   log pseudolikelihood = -10.726986  

Logistic regression                                     Number of obs = 14,986
                                                        Wald chi2(0)  =      .
                                                        Prob > chi2   =      .
Log pseudolikelihood = -10.726986                       Pseudo R2     = 0.1408

                             (Std. err. adjusted for 21 clusters in parlgov_id)
-------------------------------------------------------------------------------
              |               Robust
faces_any_fem | Coefficient  std. err.      z    P>|z|     [95% conf. interval]
--------------+----------------------------------------------------------------
 1.only_women |   .6723709   .5915452     1.14   0.256    -.4870364    1.831778
              |
   parlgov_id |
         345  |   2.129157   .1616708    13.17   0.000     1.812288    2.446026
         376  |   .8539716   .1616708     5.28   0.000     .5371027    1.170841
         543  |   1.124427   .0974088    11.54   0.000     .9335089    1.315344
         581  |   1.560762   .1616708     9.65   0.000     1.243893    1.877631
         585  |   2.061537   .1616708    12.75   0.000     1.744668    2.378406
         659  |   -.297868   .1695025    -1.76   0.079    -.6300867    .0343508
         892  |   1.650207   .1616708    10.21   0.000     1.333338    1.967076
         915  |   2.272258   .1616708    14.05   0.000     1.955389    2.589127
         967  |   3.108506   .1616708    19.23   0.000     2.791637    3.425375
         969  |   .4518717   .1616708     2.80   0.005     .1350028    .7687407
        1015  |   1.132749   .1519888     7.45   0.000     .8348568    1.430642
        1110  |   2.596358   .1576587    16.47   0.000     2.287352    2.905363
        1384  |  -.3786339   .1616708    -2.34   0.019    -.6955028   -.0617649
        1409  |   .6747962   .1616708     4.17   0.000     .3579273    .9916651
        1605  |   1.307474   .1420312     9.21   0.000     1.029098     1.58585
        2255  |    1.85316   .1563372    11.85   0.000     1.546744    2.159575
        2263  |   3.014195   .1616708    18.64   0.000     2.697326    3.331064
        2375  |   1.483182   .0483457    30.68   0.000     1.388426    1.577938
        2647  |   -.974278   .0113148   -86.11   0.000    -.9964547   -.9521014
        2751  |   .6669954   .1616708     4.13   0.000     .3501265    .9838643
              |
        _cons |  -2.454579   .1616708   -15.18   0.000    -2.771448   -2.137711
-------------------------------------------------------------------------------
Right_wing

Iteration 0:   log pseudolikelihood = -6.3293636  
Iteration 1:   log pseudolikelihood = -6.1030403  
Iteration 2:   log pseudolikelihood = -6.0898977  
Iteration 3:   log pseudolikelihood = -6.0898084  
Iteration 4:   log pseudolikelihood = -6.0898084  

Logistic regression                                     Number of obs =  1,036
                                                        Wald chi2(2)  =      .
                                                        Prob > chi2   =      .
Log pseudolikelihood = -6.0898084                       Pseudo R2     = 0.0378

                             (Std. err. adjusted for 12 clusters in parlgov_id)
-------------------------------------------------------------------------------
              |               Robust
faces_any_fem | Coefficient  std. err.      z    P>|z|     [95% conf. interval]
--------------+----------------------------------------------------------------
 1.only_women |  -.9067791   1.569026    -0.58   0.563    -3.982013    2.168454
              |
   parlgov_id |
         600  |  -.4462905   .0083766   -53.28   0.000    -.4627085   -.4298726
         993  |  -.0972167    .004854   -20.03   0.000    -.1067303    -.087703
        1072  |   .2841246   7.00e-14  4.1e+12   0.000     .2841246    .2841246
        1418  |   .4509819   3.89e-12  1.2e+11   0.000     .4509819    .4509819
        1436  |   .4102984   1.86e-12  2.2e+11   0.000     .4102984    .4102984
        1546  |   .9075022   1.90e-10  4.8e+09   0.000     .9075022    .9075022
        2091  |   .2988617   1.15e-13  2.6e+12   0.000     .2988617    .2988617
        2253  |  -.2303308   3.01e-12 -7.6e+10   0.000    -.2303308   -.2303308
        2380  |   .0216025   .0870523     0.25   0.804    -.1490168    .1922218
        2600  |  -.2113343   1.83e-12 -1.2e+11   0.000    -.2113343   -.2113343
        2623  |  -1.300772   1.08e-07 -1.2e+07   0.000    -1.300772   -1.300772
              |
        _cons |  -1.338285   5.01e-16 -2.7e+15   0.000    -1.338285   -1.338285
-------------------------------------------------------------------------------
Social_democracy

Iteration 0:   log pseudolikelihood = -21.721699  
Iteration 1:   log pseudolikelihood = -19.145624  
Iteration 2:   log pseudolikelihood = -19.118484  
Iteration 3:   log pseudolikelihood = -19.118253  
Iteration 4:   log pseudolikelihood = -19.118253  

Logistic regression                                     Number of obs = 15,036
                                                        Wald chi2(1)  =      .
                                                        Prob > chi2   =      .
Log pseudolikelihood = -19.118253                       Pseudo R2     = 0.1199

                             (Std. err. adjusted for 32 clusters in parlgov_id)
-------------------------------------------------------------------------------
              |               Robust
faces_any_fem | Coefficient  std. err.      z    P>|z|     [95% conf. interval]
--------------+----------------------------------------------------------------
 1.only_women |   1.040483   .3673059     2.83   0.005     .3205768     1.76039
              |
   parlgov_id |
         318  |   2.130727   .0387176    55.03   0.000     2.054842    2.206612
         382  |    .979552   .0387176    25.30   0.000     .9036669    1.055437
         395  |   2.676496   .0368937    72.55   0.000     2.604186    2.748807
         558  |   .4240188   .1889097     2.24   0.025     .0537626     .794275
         701  |   .9557413   .0387176    24.68   0.000     .8798563    1.031626
         706  |   1.609749   .0387176    41.58   0.000     1.533864    1.685634
         742  |    .788824   .0320251    24.63   0.000     .7260559    .8515921
         789  |   1.377754   .0153306    89.87   0.000     1.347706    1.407801
         902  |   1.322067   .0387176    34.15   0.000     1.246181    1.397952
         904  |   .7249893   .2130433     3.40   0.001     .3074322    1.142546
         945  |    1.03894   .0387176    26.83   0.000     .9630552    1.114825
         973  |   .6596679   .0154515    42.69   0.000     .6293835    .6899523
        1029  |   1.438266   .0387176    37.15   0.000     1.362381    1.514152
        1120  |   1.425417   .0363453    39.22   0.000     1.354182    1.496653
        1137  |   1.437579   .0387176    37.13   0.000     1.361694    1.513464
        1284  |   1.080904   .0387176    27.92   0.000     1.005019     1.15679
        1338  |    1.07998   .0074777   144.43   0.000     1.065324    1.094636
        1378  |    .776142   .0322193    24.09   0.000     .7129933    .8392906
        1448  |   3.014406   .0213887   140.93   0.000     2.972485    3.056327
        1493  |   2.263384   .0329601    68.67   0.000     2.198784    2.327985
        1520  |  -.5285318   .0387176   -13.65   0.000    -.6044169   -.4526467
        1556  |  -.0046931   .0352296    -0.13   0.894    -.0737418    .0643557
        1591  |   .3482264   .0387176     8.99   0.000     .2723414    .4241115
        1629  |    2.55735   .0387176    66.05   0.000     2.481465    2.633235
        1970  |   2.680573   .0343921    77.94   0.000     2.613166     2.74798
        2337  |   2.372602   .0132947   178.46   0.000     2.346545    2.398659
        2341  |   .2302577    .026968     8.54   0.000     .1774015     .283114
        2346  |   2.584982   .0387176    66.77   0.000     2.509097    2.660867
        2625  |   1.622864   .0092135   176.14   0.000     1.604806    1.640922
        2668  |   1.936571   .0387176    50.02   0.000     1.860686    2.012456
        2740  |   .7678554   .0000614  1.3e+04   0.000     .7677351    .7679758
              |
        _cons |  -1.774052   .0387176   -45.82   0.000    -1.849937   -1.698167
-------------------------------------------------------------------------------

. 
. * Output all models to latex table
. outreg2 [inter Green_Ecologist Communist_Socialist Social_democracy Christian_democracy Conservative Liberal Ri
> ght_wing] using 5.xls, replace drop(i.parlgov_id) label excel tex alpha(0.001, 0.01, 0.05, 0.1) symbol(***, **,
>  *, +)  dec(3) e(N_clust)
5.tex
5.xls
dir : seeout

. 
. 
. 
. * ###############
. * Age
. * ###############
. 
. cap drop n_ads

. quietly reg faces_age_mean c.audience_avg_age i.parlgov_id if is_img == 1  // Quietly run model to use same obs
> ervations 

. bysort parlgov_id: gen n_ads=_N if e(sample)
(49,281 missing values generated)

. 
. * Run model
. reg faces_age_mean c.audience_avg_age i.parlgov_id [iweight=1/n_ads] if is_img == 1, cluster(parlgov_id)
(sum of wgt is 51.00530983469049)

Linear regression                               Number of obs     =     13,491
                                                F(0, 146)         =          .
                                                Prob > F          =          .
                                                R-squared         =     0.3344
                                                Root MSE          =     6.4451

                               (Std. err. adjusted for 147 clusters in parlgov_id)
----------------------------------------------------------------------------------
                 |               Robust
  faces_age_mean | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------+----------------------------------------------------------------
audience_avg_age |   .0802796   .0204297     3.93   0.000     .0399035    .1206558
                 |
      parlgov_id |
             47  |  -3.855006   .2228142   -17.30   0.000    -4.295363   -3.414648
             50  |   .8966217   .2041123     4.39   0.000     .4932252    1.300018
            113  |   2.891667   .5824798     4.96   0.000     1.740486    4.042849
            118  |  -6.012219   .4489572   -13.39   0.000    -6.899514   -5.124925
            161  |  -16.03012    .138441  -115.79   0.000    -16.30373   -15.75652
            196  |  -3.747078   .2106174   -17.79   0.000     -4.16333   -3.330825
            200  |   5.237915   .3671255    14.27   0.000     4.512348    5.963482
            220  |   -1.98166   .4345706    -4.56   0.000    -2.840522   -1.122798
            235  |  -6.130537   .5033032   -12.18   0.000    -7.125238   -5.135836
            256  |  -7.673916   .3363596   -22.81   0.000    -8.338679   -7.009153
            276  |  -9.090436   .2543704   -35.74   0.000     -9.59316   -8.587712
            280  |  -5.558282   .2861776   -19.42   0.000    -6.123868   -4.992696
            282  |  -6.651821   .4599757   -14.46   0.000    -7.560892    -5.74275
            306  |  -5.425601   .3108598   -17.45   0.000    -6.039968   -4.811235
            310  |  -7.122561   .0756227   -94.19   0.000    -7.272017   -6.973104
            311  |  -11.56055   .0795337  -145.35   0.000    -11.71773   -11.40336
            318  |  -4.014563   .1450846   -27.67   0.000      -4.3013   -3.727825
            345  |  -2.581819    .222791   -11.59   0.000    -3.022131   -2.141507
            357  |   -3.84205    .554897    -6.92   0.000    -4.938718   -2.745381
            360  |  -2.697431   .3173471    -8.50   0.000    -3.324618   -2.070243
            363  |  -2.157571   .2601658    -8.29   0.000    -2.671748   -1.643393
            376  |  -8.959679     .04914  -182.33   0.000    -9.056797   -8.862562
            382  |   .2883769   .3118702     0.92   0.357    -.3279864    .9047402
            395  |  -3.371587   .4069426    -8.29   0.000    -4.175846   -2.567327
            403  |  -3.701668   .3112647   -11.89   0.000    -4.316834   -3.086501
            417  |  -4.590649    .450739   -10.18   0.000    -5.481465   -3.699833
            437  |   4.351346   .4716667     9.23   0.000     3.419169    5.283522
            438  |  -11.05739   .2687648   -41.14   0.000    -11.58856   -10.52622
            457  |  -5.910361   .0616906   -95.81   0.000    -6.032283   -5.788439
            465  |   9.962596   .5474643    18.20   0.000     8.880618    11.04457
            467  |  -6.791379   .2179763   -31.16   0.000    -7.222176   -6.360583
            501  |  -1.935823    .315426    -6.14   0.000    -2.559214   -1.312432
            512  |  -7.053971   .2742455   -25.72   0.000    -7.595975   -6.511967
            520  |  -3.951077   .1819457   -21.72   0.000    -4.310665    -3.59149
            528  |   5.755127   .2559258    22.49   0.000     5.249329    6.260925
            543  |  -3.578399   .2097924   -17.06   0.000    -3.993021   -3.163777
            558  |  -3.230181   .2399012   -13.46   0.000    -3.704308   -2.756053
            572  |   -3.20544   .3087638   -10.38   0.000    -3.815664   -2.595216
            581  |   .4310573   .4791459     0.90   0.370    -.5159006    1.378015
            585  |  -3.878576   .4143531    -9.36   0.000    -4.697481   -3.059671
            590  |  -3.707355   .3199736   -11.59   0.000    -4.339733   -3.074976
            596  |   4.365041   .4620149     9.45   0.000      3.45194    5.278143
            600  |  -.3112597   .3287432    -0.95   0.345    -.9609698    .3384504
            645  |  -4.939099   .4601696   -10.73   0.000    -5.848553   -4.029645
            657  |  -4.514098   .4540755    -9.94   0.000    -5.411508   -3.616688
            659  |   -5.54527   .3578585   -15.50   0.000    -6.252522   -4.838018
            701  |  -4.626283   .3009143   -15.37   0.000    -5.220993   -4.031572
            706  |  -1.991041   .3280553    -6.07   0.000    -2.639392   -1.342691
            723  |  -5.935423   .3162062   -18.77   0.000    -6.560356    -5.31049
            742  |   .1998288   .4023943     0.50   0.620    -.5954415    .9950991
            756  |  -7.813657   .2043578   -38.24   0.000    -8.217539   -7.409775
            757  |  -1.218037   .3505143    -3.47   0.001    -1.910774   -.5252993
            772  |  -6.432157   .2280383   -28.21   0.000     -6.88284   -5.981475
            773  |  -7.469317   .3221265   -23.19   0.000     -8.10595   -6.832684
            789  |   4.103185   .3832984    10.70   0.000     3.345655    4.860715
            791  |  -.4423893   .2494143    -1.77   0.078     -.935318    .0505395
            829  |   -4.35018   .2473338   -17.59   0.000    -4.838998   -3.861363
            851  |  -1.010207   .5203463    -1.94   0.054    -2.038591    .0181772
            865  |  -4.277569   .2692732   -15.89   0.000    -4.809746   -3.745392
            882  |  -3.675915   .2514519   -14.62   0.000    -4.172871   -3.178959
            892  |  -7.137399   .3326726   -21.45   0.000    -7.794875   -6.479923
            902  |  -9.514694   .1769283   -53.78   0.000    -9.864366   -9.165023
            904  |  -3.996918   .3505961   -11.40   0.000    -4.689817   -3.304019
            915  |   -3.05975   .2125463   -14.40   0.000    -3.479815   -2.639685
            945  |  -3.298363   .2804521   -11.76   0.000    -3.852633   -2.744093
            967  |  -.0636627   .1943797    -0.33   0.744    -.4478241    .3204987
            969  |  -1.392914    .365717    -3.81   0.000    -2.115697   -.6701309
            973  |   -7.49407   .3511802   -21.34   0.000    -8.188123   -6.800017
            984  |  -8.153419   .2970582   -27.45   0.000    -8.740508   -7.566329
            990  |  -9.974271   .2938821   -33.94   0.000    -10.55508   -9.393458
            993  |  -5.386495   .2403348   -22.41   0.000     -5.86148   -4.911511
           1013  |   1.573388    .365617     4.30   0.000     .8508025    2.295974
           1015  |  -1.512312   .4369128    -3.46   0.001    -2.375803   -.6488216
           1029  |  -7.537611   .3225478   -23.37   0.000    -8.175077   -6.900145
           1045  |  -4.396762   .3143821   -13.99   0.000     -5.01809   -3.775435
           1062  |  -4.817453   .2107532   -22.86   0.000    -5.233974   -4.400931
           1072  |  -.0141273   .2959081    -0.05   0.962     -.598944    .5706895
           1110  |  -3.874059   .3686475   -10.51   0.000    -4.602634   -3.145484
           1118  |  -3.100215   .3978512    -7.79   0.000    -3.886506   -2.313923
           1120  |   -3.32859   .3314568   -10.04   0.000    -3.983663   -2.673517
           1137  |    1.85234   .1344211    13.78   0.000     1.586678    2.118003
           1154  |  -3.386501   .0124405  -272.22   0.000    -3.411088   -3.361914
           1192  |  -7.523641    .179205   -41.98   0.000    -7.877812    -7.16947
           1206  |  -7.262656    .265478   -27.36   0.000    -7.787332   -6.737979
           1234  |   .2508585   .0755888     3.32   0.001     .1014689     .400248
           1245  |  -3.505959   .2750077   -12.75   0.000    -4.049469   -2.962449
           1277  |  -2.856446   .4643984    -6.15   0.000    -3.774258   -1.938634
           1292  |  -.8369342    .004205  -199.03   0.000    -.8452447   -.8286236
           1338  |  -7.284147   .6272215   -11.61   0.000    -8.523754   -6.044541
           1361  |   4.280367   .3139086    13.64   0.000     3.659975    4.900759
           1378  |  -5.278443   .3475634   -15.19   0.000    -5.965348   -4.591537
           1384  |  -.8856827     .34964    -2.53   0.012    -1.576692   -.1946732
           1409  |   1.390498   .2252915     6.17   0.000     .9452439    1.835752
           1418  |  -7.418758   .3877168   -19.13   0.000     -8.18502   -6.652495
           1421  |    -3.7619   .1486717   -25.30   0.000    -4.055727   -3.468073
           1429  |  -3.720563   .0248627  -149.64   0.000      -3.7697   -3.671425
           1432  |  -.3205697   .4279568    -0.75   0.455     -1.16636    .5252208
           1436  |   6.279091   .3820951    16.43   0.000     5.523939    7.034243
           1448  |  -.3419271   .2885555    -1.18   0.238    -.9122126    .2283584
           1461  |  -3.678165   .3881828    -9.48   0.000    -4.445348   -2.910981
           1463  |  -1.994452   .6892229    -2.89   0.004    -3.356595   -.6323095
           1465  |   4.988444   .4764178    10.47   0.000     4.046878    5.930011
           1493  |   1.570199   .0365664    42.94   0.000     1.497931    1.642467
           1520  |  -10.45428   .2887946   -36.20   0.000    -11.02504   -9.883521
           1521  |  -2.001796    .243864    -8.21   0.000    -2.483756   -1.519837
           1546  |  -6.611458   .3679445   -17.97   0.000    -7.338643   -5.884272
           1556  |  -5.462879   .3729398   -14.65   0.000    -6.199937   -4.725821
           1575  |   -6.14688   .0939297   -65.44   0.000    -6.332518   -5.961242
           1591  |  -.0550765   .2704218    -0.20   0.839    -.5895235    .4793705
           1592  |  -7.578052   .1930517   -39.25   0.000    -7.959589   -7.196515
           1594  |  -2.853825     .22632   -12.61   0.000    -3.301112   -2.406538
           1597  |    8.24924   .3082575    26.76   0.000     7.640016    8.858463
           1605  |   -5.20431   .4272795   -12.18   0.000    -6.048762   -4.359858
           1620  |   1.597179   .4029403     3.96   0.000     .8008293    2.393528
           1629  |  -5.412718   .3346949   -16.17   0.000     -6.07419   -4.751245
           1644  |  -5.189379   .4019432   -12.91   0.000    -5.983758   -4.395001
           1666  |   1.869035   .1777363    10.52   0.000     1.517767    2.220304
           1727  |  -5.037284    .118671   -42.45   0.000    -5.271819   -4.802749
           1759  |  -1.813809   .1947289    -9.31   0.000    -2.198661   -1.428958
           1970  |  -7.378597   .5351316   -13.79   0.000    -8.436202   -6.320992
           2091  |    1.91063   .1959319     9.75   0.000     1.523401    2.297859
           2154  |  -8.387088   .4151535   -20.20   0.000    -9.207575   -7.566602
           2155  |  -17.53073   .4354911   -40.26   0.000    -18.39141   -16.67005
           2255  |  -11.25695   .0380754  -295.65   0.000     -11.3322    -11.1817
           2256  |   -8.02806   .2077737   -38.64   0.000    -8.438693   -7.617427
           2261  |  -7.888434   .1881936   -41.92   0.000     -8.26037   -7.516499
           2263  |   12.35267   .3803349    32.48   0.000       11.601    13.10435
           2337  |  -3.779764   .3224248   -11.72   0.000    -4.416987   -3.142542
           2341  |  -5.652499   .3980866   -14.20   0.000    -6.439255   -4.865742
           2375  |  -7.660926   .3903265   -19.63   0.000    -8.432346   -6.889506
           2395  |   4.437855   .4364163    10.17   0.000     3.575345    5.300364
           2600  |  -.7418396   .1878475    -3.95   0.000    -1.113091   -.3705881
           2623  |   3.920201   .3207371    12.22   0.000     3.286313    4.554088
           2625  |  -8.345193   .2934679   -28.44   0.000    -8.925187   -7.765198
           2647  |  -3.849981   .2940628   -13.09   0.000    -4.431151   -3.268811
           2659  |  -10.10083   .4298064   -23.50   0.000    -10.95027   -9.251381
           2668  |  -7.028633   .4088564   -17.19   0.000    -7.836675   -6.220592
           2670  |  -7.596757   .4280571   -17.75   0.000    -8.442746   -6.750769
           2717  |  -.4577324   .3532937    -1.30   0.197    -1.155963    .2404981
           2724  |   2.229959    .264147     8.44   0.000     1.707913    2.752004
           2729  |    6.59922   .4924681    13.40   0.000     5.625932    7.572507
           2730  |  -9.627139   .4242384   -22.69   0.000    -10.46558   -8.788697
           2737  |   6.219191   .2446495    25.42   0.000     5.735679    6.702703
           2740  |  -7.811737   .1093744   -71.42   0.000    -8.027899   -7.595576
           2750  |  -.2401963    .205155    -1.17   0.244    -.6456536    .1652609
           2751  |  -1.179872   .2576084    -4.58   0.000    -1.688995   -.6707484
                 |
           _cons |   36.70922   .5370126    68.36   0.000      35.6479    37.77054
----------------------------------------------------------------------------------

. est store inter

. 
. * Calculate margins
. margins, at(audience_avg_age = (18 (5) 70) )

Predictive margins                                      Number of obs = 13,491
Model VCE: Robust

Expression: Linear prediction, predict()
1._at:  audience_avg_age = 18
2._at:  audience_avg_age = 23
3._at:  audience_avg_age = 28
4._at:  audience_avg_age = 33
5._at:  audience_avg_age = 38
6._at:  audience_avg_age = 43
7._at:  audience_avg_age = 48
8._at:  audience_avg_age = 53
9._at:  audience_avg_age = 58
10._at: audience_avg_age = 63
11._at: audience_avg_age = 68

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
         _at |
          1  |   35.65095   .4828391    73.84   0.000     34.69669    36.60521
          2  |   36.05235   .3806906    94.70   0.000     35.29997    36.80473
          3  |   36.45375   .2785422   130.87   0.000     35.90325    37.00424
          4  |   36.85515   .1763937   208.94   0.000     36.50653    37.20376
          5  |   37.25654   .0742453   501.80   0.000     37.10981    37.40328
          6  |   37.65794   .0279032  1349.59   0.000      37.6028    37.71309
          7  |   38.05934   .1300516   292.65   0.000     37.80231    38.31637
          8  |   38.46074   .2322001   165.64   0.000     38.00183    38.91965
          9  |   38.86214   .3343485   116.23   0.000     38.20135    39.52292
         10  |   39.26353    .436497    89.95   0.000     38.40087     40.1262
         11  |   39.66493   .5386454    73.64   0.000     38.60038    40.72948
------------------------------------------------------------------------------

. 
. * Plot margins
. marginsplot, xtitle("Average audience age", size(vlarge)) title(,size(vlarge)) ytitle( "Mean age on image", siz
> e(vlarge)) title("" )   plot1opts(lcolor(gs8)) ciopt(color(black%20) msize(large)) recastci(rarea) recast(line)
>  xlabel(#5,labsize(large)) ylabel(,labsize(large)) 

Variables that uniquely identify margins: audience_avg_age

. graph export "figure_g5_marginsplot_age.pdf", replace
file figure_g5_marginsplot_age.pdf saved as PDF format

. 
. 
. * Run models for each party family
. levelsof pg_party_family_name if inlist(pg_party_family_name,  "Green_Ecologist","Communist_Socialist", "Social
> _democracy", "Christian_democracy", "Conservative", "Liberal", "Right_wing"), local(groups)
`"Christian_democracy"' `"Communist_Socialist"' `"Conservative"' `"Green_Ecologist"' `"Liberal"' `"Right_wing"' `
> "Social_democracy"'

. local estimates_list // 

. foreach g of local groups {
  2.     reg faces_age_mean c.audience_avg_age i.parlgov_id [iweight=1/n_ads] if pg_party_family_name ==  "`g'", 
> cluster(parlgov_id)
  3.     est store `g'
  4. }
(sum of wgt is 5.896353919349425)

Linear regression                               Number of obs     =        728
                                                F(0, 15)          =          .
                                                Prob > F          =          .
                                                R-squared         =     0.3769
                                                Root MSE          =     5.4731

                                (Std. err. adjusted for 16 clusters in parlgov_id)
----------------------------------------------------------------------------------
                 |               Robust
  faces_age_mean | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------+----------------------------------------------------------------
audience_avg_age |   .1396933   .0726049     1.92   0.074    -.0150604    .2944471
                 |
      parlgov_id |
            235  |   -3.09125    .996828    -3.10   0.007    -5.215939   -.9665617
            276  |  -5.327202   .1121474   -47.50   0.000    -5.566239   -5.088166
            282  |  -3.486529   .8428464    -4.14   0.001    -5.283014   -1.690044
            723  |   -2.35202   .3319054    -7.09   0.000     -3.05946   -1.644581
           1013  |   5.013094   .5075058     9.88   0.000     3.931371    6.094817
           1192  |  -3.541811   .1549822   -22.85   0.000    -3.872148   -3.211475
           1206  |  -3.531725   .1516227   -23.29   0.000    -3.854901   -3.208549
           1234  |   4.534025   .5232232     8.67   0.000     3.418801    5.649249
           1245  |    .197257   .1854903     1.06   0.304    -.1981062    .5926203
           1361  |   7.870452   .3237397    24.31   0.000     7.180417    8.560487
           1432  |    2.93784   .7290548     4.03   0.001     1.383896    4.491783
           1463  |   .5041426   1.657566     0.30   0.765    -3.028877    4.037162
           1727  |  -.8794095   .3701134    -2.38   0.031    -1.668288   -.0905314
           2395  |   7.671662   .7591191    10.11   0.000     6.053638    9.289686
           2750  |   3.666166   .0627586    58.42   0.000     3.532399    3.799932
                 |
           _cons |   30.64449   2.700343    11.35   0.000     24.88884    36.40013
----------------------------------------------------------------------------------
(sum of wgt is 3.613604947577118)

Linear regression                               Number of obs     =        364
                                                F(0, 12)          =          .
                                                Prob > F          =          .
                                                R-squared         =     0.3949
                                                Root MSE          =      7.524

                                (Std. err. adjusted for 13 clusters in parlgov_id)
----------------------------------------------------------------------------------
                 |               Robust
  faces_age_mean | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------+----------------------------------------------------------------
audience_avg_age |   .1785283    .111701     1.60   0.136    -.0648473    .4219038
                 |
      parlgov_id |
            256  |  -1.120202   .6156369    -1.82   0.094     -2.46156    .2211552
            306  |   1.250744    .755059     1.66   0.124    -.3943887    2.895876
            357  |   1.660693   .5792346     2.87   0.014     .3986496    2.922737
            457  |   2.557619   2.792009     0.92   0.378    -3.525645    8.640883
            465  |   15.50108   .5385956    28.78   0.000     14.32759    16.67458
            572  |   3.480984   .7665191     4.54   0.001     1.810883    5.151086
            791  |   6.529454   1.091017     5.98   0.000     4.152331    8.906576
            882  |   3.286129   1.079877     3.04   0.010     .9332798    5.638978
           1292  |   7.354592   2.477701     2.97   0.012     1.956144    12.75304
           1592  |  -.3351558   1.399184    -0.24   0.815    -3.383716    2.713404
           2670  |  -1.484027   .1142733   -12.99   0.000    -1.733007   -1.235047
           2724  |    9.13095   1.010465     9.04   0.000     6.929337    11.33256
                 |
           _cons |   25.95537    5.39087     4.81   0.000     14.20967    37.70106
----------------------------------------------------------------------------------
(sum of wgt is 10.20210433726114)

Linear regression                               Number of obs     =      1,985
                                                F(0, 27)          =          .
                                                Prob > F          =          .
                                                R-squared         =     0.3756
                                                Root MSE          =     6.4004

                                (Std. err. adjusted for 28 clusters in parlgov_id)
----------------------------------------------------------------------------------
                 |               Robust
  faces_age_mean | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------+----------------------------------------------------------------
audience_avg_age |   .0655672   .0446978     1.47   0.154    -.0261451    .1572796
                 |
      parlgov_id |
            280  |  -5.352191   .6261239    -8.55   0.000    -6.636891   -4.067491
            363  |  -1.970213   .5692131    -3.46   0.002    -3.138141   -.8022839
            417  |   -4.26605   .9861653    -4.33   0.000    -6.289494   -2.242606
            437  |   4.691016   1.031953     4.55   0.000     2.573624    6.808408
            438  |  -10.86384   .5880266   -18.48   0.000    -12.07037   -9.657308
            501  |  -1.708669   .6901159    -2.48   0.020     -3.12467   -.2926686
            512  |  -6.856473   .6000178   -11.43   0.000    -8.087608   -5.625339
            528  |   5.939432   .5599364    10.61   0.000     4.790537    7.088326
            590  |  -3.476926   .7000656    -4.97   0.000    -4.913342    -2.04051
            596  |   4.697761   1.010836     4.65   0.000     2.623697    6.771824
            645  |  -4.607708   1.006798    -4.58   0.000    -6.673488   -2.541929
            657  |  -4.187096   .9934653    -4.21   0.000    -6.225519   -2.148674
            773  |  -7.237338   .7047758   -10.27   0.000    -8.683419   -5.791258
            829  |  -4.172063   .5411381    -7.71   0.000    -5.282387    -3.06174
            851  |  -.6354804   1.138458    -0.56   0.581    -2.971403    1.700443
            984  |  -7.939493   .6499293   -12.22   0.000    -9.273037   -6.605948
           1045  |  -4.170361    .687832    -6.06   0.000    -5.581675   -2.759046
           1118  |  -2.813703   .8704529    -3.23   0.003    -4.599725   -1.027681
           1421  |  -3.654834   .3252766   -11.24   0.000    -4.322247   -2.987422
           1575  |  -6.079237   .2055075   -29.58   0.000    -6.500903    -5.65757
           1597  |   8.471231   .6744322    12.56   0.000      7.08741    9.855051
           1620  |   1.887355   .8815872     2.14   0.041     .0784879    3.696223
           1666  |   1.997032   .3888667     5.14   0.000     1.199143     2.79492
           1759  |  -1.673576   .4260444    -3.93   0.001    -2.547747   -.7994048
           2154  |  -8.088116   .9083082    -8.90   0.000    -9.951811   -6.224422
           2659  |  -9.791302   .9403673   -10.41   0.000    -11.72078   -7.861828
           2717  |  -.2033085   .7729661    -0.26   0.795    -1.789304    1.382687
                 |
           _cons |   37.09595   1.174922    31.57   0.000     34.68521    39.50669
----------------------------------------------------------------------------------
(sum of wgt is 3.681347965956981)

Linear regression                               Number of obs     =      1,149
                                                F(0, 12)          =          .
                                                Prob > F          =          .
                                                R-squared         =     0.0799
                                                Root MSE          =     6.9321

                                (Std. err. adjusted for 13 clusters in parlgov_id)
----------------------------------------------------------------------------------
                 |               Robust
  faces_age_mean | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------+----------------------------------------------------------------
audience_avg_age |   .1411107   .0993701     1.42   0.181    -.0753981    .3576195
                 |
      parlgov_id |
            196  |   12.06813    .351066    34.38   0.000     11.30323    12.83304
            310  |   9.094609   .3055483    29.76   0.000     8.428876    9.760341
            360  |   12.79999   .8701999    14.71   0.000     10.90398    14.69599
            403  |   11.81386   .8406148    14.05   0.000     9.982317     13.6454
            467  |   9.001921   .3868598    23.27   0.000     8.159026    9.844816
            756  |   8.020194   .3206197    25.01   0.000     7.321623    8.718764
            772  |   9.331183   .4358016    21.41   0.000     8.381653    10.28071
           1062  |   10.99735   .3517269    31.27   0.000     10.23101     11.7637
           1154  |   13.09288   .7338878    17.84   0.000     11.49388    14.69189
           1429  |   12.64775    .552445    22.89   0.000     11.44407    13.85142
           1594  |   12.91463   .4274439    30.21   0.000     11.98331    13.84595
           1644  |   10.05615   1.281675     7.85   0.000     7.263615    12.84868
                 |
           _cons |   18.66788   3.285408     5.68   0.000     11.50959    25.82617
----------------------------------------------------------------------------------
(sum of wgt is 6.885980007234858)

Linear regression                               Number of obs     =      2,461
                                                F(0, 21)          =          .
                                                Prob > F          =          .
                                                R-squared         =     0.3037
                                                Root MSE          =     7.0614

                                (Std. err. adjusted for 22 clusters in parlgov_id)
----------------------------------------------------------------------------------
                 |               Robust
  faces_age_mean | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------+----------------------------------------------------------------
audience_avg_age |   .0711512    .071634     0.99   0.332    -.0778198    .2201222
                 |
      parlgov_id |
            345  |  -5.634204   1.261201    -4.47   0.000    -8.257014   -3.011393
            376  |  -12.13357   2.214691    -5.48   0.000    -16.73927   -7.527867
            543  |  -6.636591   1.306779    -5.08   0.000    -9.354186   -3.918996
            581  |  -2.506782   .3623266    -6.92   0.000    -3.260281   -1.753282
            585  |  -6.845366   .5895139   -11.61   0.000    -8.071327   -5.619404
            659  |  -8.537303   .7876049   -10.84   0.000    -10.17522   -6.899389
            892  |  -10.14069   .8759157   -11.58   0.000    -11.96225   -8.319119
            915  |  -6.116712   1.297122    -4.72   0.000    -8.814226   -3.419198
            967  |  -3.128742   1.360821    -2.30   0.032    -5.958725   -.2987586
            969  |  -4.381436   .7600501    -5.76   0.000    -5.962046   -2.800825
           1015  |  -4.469022   .5104115    -8.76   0.000    -5.530481   -3.407563
           1110  |  -6.861271   .7497744    -9.15   0.000    -8.420512    -5.30203
           1384  |  -3.881388   .8164218    -4.75   0.000     -5.57923   -2.183546
           1409  |  -1.660769   1.252433    -1.33   0.199    -4.265347    .9438085
           1605  |  -8.165324   .5441893   -15.00   0.000    -9.297028    -7.03362
           2255  |  -14.42589   2.175894    -6.63   0.000    -18.95091   -9.900872
           2263  |   9.370684   .7087942    13.22   0.000     7.896666     10.8447
           2375  |  -10.63845     .67376   -15.79   0.000    -12.03961   -9.237291
           2647  |  -6.870519   1.011296    -6.79   0.000    -8.973625   -4.767414
           2737  |   3.176574   1.184557     2.68   0.014     .7131529    5.639995
           2751  |  -4.216699   1.139118    -3.70   0.001    -6.585625   -1.847772
                 |
           _cons |    40.1011   3.925351    10.22   0.000     31.93789    48.26432
----------------------------------------------------------------------------------
(sum of wgt is 3.546571245186764)

Linear regression                               Number of obs     =        390
                                                F(0, 9)           =          .
                                                Prob > F          =          .
                                                R-squared         =     0.3746
                                                Root MSE          =     5.3878

                                (Std. err. adjusted for 10 clusters in parlgov_id)
----------------------------------------------------------------------------------
                 |               Robust
  faces_age_mean | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------+----------------------------------------------------------------
audience_avg_age |   .0895109   .0416211     2.15   0.060    -.0046425    .1836643
                 |
      parlgov_id |
            600  |  -1.264196   .2539084    -4.98   0.001    -1.838577   -.6898156
            993  |  -6.299484   .0737955   -85.36   0.000    -6.466421   -6.132547
           1072  |  -.9522273   .1870141    -5.09   0.001    -1.375283   -.5291719
           1418  |  -8.398342   .3740545   -22.45   0.000    -9.244512   -7.552172
           1436  |   5.302047   .3626014    14.62   0.000     4.481786    6.122308
           1546  |  -7.582107   .3337727   -22.72   0.000    -8.337154   -6.827061
           2091  |   1.017704   .0166658    61.07   0.000     .9800038    1.055405
           2600  |  -1.631112   .0331361   -49.22   0.000    -1.706071   -1.556153
           2623  |   2.970882   .2375977    12.50   0.000     2.433398    3.508365
                 |
           _cons |   37.27096   1.509882    24.68   0.000     33.85537    40.68655
----------------------------------------------------------------------------------
(sum of wgt is 13.39917017240045)

Linear regression                               Number of obs     =      6,029
                                                F(0, 30)          =          .
                                                Prob > F          =          .
                                                R-squared         =     0.2036
                                                Root MSE          =     6.5615

                                (Std. err. adjusted for 31 clusters in parlgov_id)
----------------------------------------------------------------------------------
                 |               Robust
  faces_age_mean | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-----------------+----------------------------------------------------------------
audience_avg_age |     .05995   .0292854     2.05   0.049     .0001412    .1197588
                 |
      parlgov_id |
            318  |  -2.320971   .4149707    -5.59   0.000    -3.168454   -1.473488
            382  |   2.147937   .1758878    12.21   0.000     1.788727    2.507148
            395  |  -1.417419    .039604   -35.79   0.000    -1.498301   -1.336537
            558  |  -1.442237   .2790535    -5.17   0.000     -2.01214   -.8723333
            701  |  -2.777624   .1915928   -14.50   0.000    -3.168909    -2.38634
            706  |  -.1153749   .1526869    -0.76   0.456    -.4272031    .1964533
            742  |    2.14947   .0461238    46.60   0.000     2.055273    2.243668
            789  |   6.033824   .0734973    82.10   0.000     5.883722    6.183926
            902  |  -7.789415   .3693236   -21.09   0.000    -8.543674   -7.035155
            904  |  -2.098821   .1203752   -17.44   0.000     -2.34466   -1.852982
            945  |  -1.470067   .2209248    -6.65   0.000    -1.921255   -1.018878
            973  |  -5.595392    .119538   -46.81   0.000    -5.839521   -5.351263
           1029  |  -5.667425   .1605817   -35.29   0.000    -5.995377   -5.339473
           1120  |  -1.449538    .147811    -9.81   0.000    -1.751409   -1.147668
           1137  |   3.535321   .4302566     8.22   0.000     2.656619    4.414022
           1277  |  -.8451041   .0427574   -19.77   0.000    -.9324263   -.7577819
           1338  |   -5.11078     .27616   -18.51   0.000    -5.674774   -4.546786
           1378  |  -3.383363   .1247225   -27.13   0.000    -3.638081   -3.128646
           1448  |   1.494433   .2093088     7.14   0.000     1.066967    1.921899
           1493  |   3.155804   .5705286     5.53   0.000     1.990629    4.320979
           1520  |  -8.617681   .2089662   -41.24   0.000    -9.044447   -8.190915
           1556  |  -3.542548   .0883462   -40.10   0.000    -3.722975   -3.362121
           1591  |   1.763239    .235303     7.49   0.000     1.282686    2.243791
           1629  |  -3.530444   .1431692   -24.66   0.000    -3.822835   -3.238054
           1970  |  -5.296868   .1441516   -36.75   0.000    -5.591265   -5.002471
           2337  |  -1.909701   .1607582   -11.88   0.000    -2.238013   -1.581389
           2341  |  -3.707144   .0522989   -70.88   0.000    -3.813952   -3.600335
           2625  |  -6.503944   .2022671   -32.16   0.000    -6.917029    -6.09086
           2668  |  -5.072562   .0368606  -137.61   0.000    -5.147841   -4.997282
           2740  |  -6.153681   .4661603   -13.20   0.000    -7.105707   -5.201655
                 |
           _cons |   35.69439   1.392739    25.63   0.000     32.85003    38.53874
----------------------------------------------------------------------------------

. 
. * Output all models to latex table
. outreg2 [inter Green_Ecologist Communist_Socialist Social_democracy Christian_democracy Conservative Liberal Ri
> ght_wing] using age.xls, replace drop(i.parlgov_id) label excel tex alpha(0.001, 0.01, 0.05, 0.1) symbol(***, *
> *, *, +)  dec(3) e(N_clust)
age.tex
age.xls
dir : seeout

. 
. log close
      name:  <unnamed>
       log:  C:\Users\scripts\Downloads\main-models-stata.log
  log type:  text
 closed on:  27 Jan 2025, 15:43:50
-----------------------------------------------------------------------------------------------------------------
